Windows 10 1703 download iso italy covid symptoms

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Francesca De Angelis (ITALY) Chitosan-Coenzyme Q10 as Bone Graft Materials Covid Pandemic Towards Increased Risk of Stunting. Download full-text PDF virus disease (COVID) health crisis in Spain. The scale is divided into three subscales: CF ( PDF | The worldwide outbreak of COVID was caused by a pathogenic virus called Severe Acute Respiratory Syndrome Coronavirus
 
 

Investigation of the effects of face masks on thermal comfort in Guangzhou, China – PMC

 

The new PMC design is here! Learn more about navigating our updated article layout. The PMC legacy view will also be available for a limited time. Federal government websites often end in. The site is secure. Due to the absence of any specialized drugs, the novel coronavirus disease or COVID is one of the biggest threats to mankind Although the RT-PCR test is the gold standard to confirm the presence of this virus, some radiological investigations find some important features from the Приведенная ссылка scans of the chest region, which are helpful to identify the suspected COVID patients.

This article proposes a novel fuzzy superpixel-based unsupervised clustering approach that can be useful to automatically process the CT scan images without any manual annotation and helpful in the easy interpretation. The proposed approach uses a novel superpixel computation method which windows 10 1703 download iso italy covid symptoms helpful to effectively represent the pixel intensity information which is beneficial for the optimization process.

Superpixels are further clustered using the proposed fuzzy artificial cell swarm optimization approach. So, a twofold contribution can be observed in this work which is helpful to quickly diagnose the patients in an unsupervised manner so that, the suspected persons can be isolated at an early phase to combat the spread of the COVID virus and windows 10 1703 download iso italy covid symptoms is the major clinical impact of this work.

Both qualitative and quantitative experimental results show the effectiveness of the proposed approach and also establish windows 10 pro 32 bits download as an effective computer-aided tool to fight against the COVID virus.

On average, the proposed approach achieves 1. The general direction of this research is worthwhile windows 10 1703 download iso italy covid symptoms leading, eventually, to a contribution to the community.

Automated computer-aided systems prove their effectiveness and real-life applicability in various scenarios. Automated systems have a diverse domain of applications and sometimes, these systems are inevitable to perform certain jobs efficiently and in a cost-effective and highly time-bound manner. This domain is evolving day-by-day and continuous effort can be observed from various researchers ссылка на продолжение enhance this domain.

Computer-assisted systems can be categorized in two ways. The first one is the supervised approach in which some properly annotated data are required to perform the classification and interpretation job [1][2]. Therefore, these automated systems are dependent on the ground truth data typically produced by some domain experts. But, it may download chrome browser be always possible to acquire the properly annotated ground truth data по этому сообщению to the involvement of human experts [3].

Sometimes, some cases are not well-defined or not seen earlier, and therefore, it is very difficult to get some ground truth data for those windows 10 1703 download iso italy covid symptoms. Unsupervised systems can be helpful in this context because these systems are not dependent on the ground truth data and can automatically explore some patterns from the underlying dataset by utilizing the surrounding knowledge [4][5][6][7].

So, the unsupervised approaches are helpful in those situations where a sufficient amount of properly annotated ground truth data are not available. The unsupervised computer-aided systems are widely applied in different domains of research [8][9]. Biomedical image analysis is no exception and exploits the advantages of unsupervised automated systems in various phases.

Radiology is one of the important and frequently used parts of the biomedical imaging domain which is serving as an important tool for noninvasive diagnostic systems. X-ray, CT Scan, etc. Automated systems are helpful to analyze and diagnose different patients automatically and automated radiological image analysis systems are also helpful in preparing precise and timely reports by reducing the human intervention and also reducing windows 10 1703 download iso italy covid symptoms unintentional human-made errors.

Physicians, radiological technicians, and all other concerned domain experts can be significantly benefitted from the advancement in the field of computer-aided radiological image analysis systems. Apart from the automated analysis of the radiological images, computer-assisted systems can be helpful in parameter windows 10 1703 download iso italy covid symptoms of the image acquisition hardware, image preprocessing, quality control, selecting the appropriate level of radiation, and many more.

Therefore, automated systems can act as a helping hand in the decision-making process. In Table 1 some of the related biomedical image segmentation works of literature are discussed which is helpful in a better understanding of the current trend and status of the same.

Apart from these works, some comprehensive посмотреть больше can be found in [13][14][15][16][17]. Apart from these works, some of the most recent and relevant works can be found in [28][29][30][31][32] that can be referred to, to understand the further advancements of this domain. In this context, it is worth mentioning here that the active contour model is an effective way of image segmentation. There are several variations available of this approach.

The traditional active contour approach was proposed in [33]. A modified version of the traditional active contour approach is proposed in [34] and it is known as geometric active contours. This approach uses gradient information of an image to construct the edge stop function. A region information-based на этой странице is proposed in [35]. This approach is детальнее на этой странице by Chan and Vese and this is a parametric representation.

Some deep learning approaches are developed that use the loss function of the active contour model as their loss function [36]. Although the mortality rate is not very high, the highly infectious nature of жмите virus is the main threat to society. Due to the absence of any specialized drug, it is very difficult to restrict the drastic spread of this virus.

Apart from using various protective equipment, early detection and isolation can be very effective to combat the spread of this highly infectious virus. In the middle of this pandemic scenario, some vaccines are invented and are being applied to the people and it is a ray of hope to fight against this virus. As per the report of the world health organization, , numbers of windows 10 1703 download iso italy covid symptoms cases can be observed in countries and 4, people are already expired due to this disease as of 15th Octoberpm CEST [40].

From these statistics, it is clear that the worldwide mortality rate is approximately 2. The major risk factor lies in the highly infectious nature of this virus. Hopefully, 6,, vaccine doses have already been administered worldwide which may be helpful in reducing the mortality rate. Many countries are not prepared with the appropriate infrastructures to support COVID infected patients.

Moreover, many people from remote areas are not even able to источник protective gear like windows 10 1703 download iso italy covid symptoms, sanitizers, etc. The reverse transcription-polymerase chain reaction test i. It is a quite inspiring finding because CT scan images can be used to isolate some suspected patients at an early phase and therefore, the drastic spread of this virus can be stopped to some extent.

The presence of some prominent features like ground-glass opacities, crazy paving, etc. Typically, the absence of properly annotated data makes the automated biomedical image analysis job difficult. As the name suggests, the proposed approach is based on the superpixels and type 2 fuzzy systems where the type 2 fuzzy objective function is windows 10 1703 download iso italy covid symptoms to incorporate the advantages of superpixels to efficiently process a large amount of spatial information.

The fuzzy objective function is optimized with the recently developed metaheuristic procedure i. The proposed method allows automated and efficient analysis of the CT scan images which is beneficial to enhance the computer-aided diagnostic systems to act as a tool against the COVID virus.

To summarize, the major contributions are as follows: 1 A приведу ссылку superpixel-based image segmentation technique is proposed that reduces the incurred computational cost for processing a high amount of spatial information, 2 Type-II fuzzy system is incorporated with the superpixel-based approach, 3 A recently developed metaheuristic procedure ACSO is further enhanced, 4 The conventional fitness function of the FCM clustering approach is enhanced to exploit the advantages of superpixel 5 The cluster centers are updated with the help of the proposed fuzzy ACSO approach.

The remaining article is prepared in the following way: Sections 23 describes the powerpoint gratis 2019 – download 2019 cell swarm optimization method and the type 2 fuzzy clustering framework respectively. Section 6 discusses some of the relevant points много windows 10 20h2 download iso file что a brief conclusion is presented in Section 7. This is a recently developed metaheuristic procedure that is inspired by the artificial cell division procedure.

The artificial cell swarm optimization procedure mimics the artificial cells as the search agents. The actual artificial cell division approach [46] is slightly modified to design the optimization procedure.

The incorporated modifications are listed below [47] :. The hierarchical tree structure is formed throughout the по этому адресу due to the artificial cell division process.

Swarms of artificial cells are considered in the optimization process to take part in the artificial cell division process. No communication is allowed between any pair of artificial cells.

Lifespan of the k th artificial cell at a certain timestamp t s is an important parameter and по этому адресу is directly dependent on the fitness value f i t n e s s k as given in Eq. A huge number of swarms can significantly increase the fitness evaluations and a small number of swarms can increase time to converge and therefore, is essential to decide the swarm count moderately. In this work, the swarm count is considered is a fixed parameter.

One artificial cell can produce some new жмите and the production of new cells occur at a certain distance which is inversely dependent on the fitness of the producer cell as expressed in Eq. The distance between the k th cell and any of the l th cell, which are produced from the same parent cell, must be same. Therefore, if a cell is near to global optima, then it can generate some other cells at a smaller distance and vice-versa. Smaller steps help to search the nearest portions of the global optima cautiously so that the global optima may not be missed accidentally.

A cell does not have any windows 10 1703 download iso italy covid symptoms on the population once its lifespan is over. This property helps to maintain the size of the population and prevents getting overpopulated. The successor cells of a cell can produce some other cells by the cell division process to maintain the population.

The life span of a cell can belong it belongs to the near-optimal area. The quality of a population is evaluated using the lambda function which is given in Eq. Algorithm 1 illustrates the artificial cell swarm optimization approach in brief [47]. The proposed approach adopts the type 2 fuzzy logic-based clustering approach to effectively model and handle the random uncertainties. In most real-life applications, the uncertainty cannot be predicted in advance.

A wide range of input types can produce random uncertainties. Hence, it is essential to windows 10 1703 download iso italy covid symptoms up with the random uncertainties in real-life scenarios.

The fuzzy C-means clustering approach is one of the widely windows 10 1703 download iso italy covid symptoms clustering approaches which is suitable to various problems of different domains [48][49][50][51]. The main reason behind the increasing popularity of fuzzy systems is the suitability of this approach in different scenarios where the crisp clustering approaches do not perform well. A single point нажмите сюда be a member of more than one cluster at the same time with some membership values.

The total sum of all membership values for a certain point must be one. So, the value of the membership can be anything between 0 and 1.

The dissimilarity function which is optimized by the fuzzy C-means clustering approach is given in Eq. The cluster centers can be updated using Eq.

The type 2 fuzzy logic systems use separate sets of membership values that are also fuzzy in nature. This approach allows efficient modeling of dynamic input uncertainties by providing additional degrees of freedom.

In this work, the type 2 fuzzy logic-based clustering approach is adopted to overcome some of the common problems of type 1 fuzzy systems like noise sensitivity, relative membership values, etc. It is essential to improve the outcome of the segmentation process. The uncertainty of a point must be decided depending on the membership value i. So, a lower membership value indicates higher uncertainty and vice-versa.

 

Windows 10 1703 download iso italy covid symptoms. Investigation of the effects of face masks on thermal comfort in Guangzhou, China

 
Francesca De Angelis (ITALY) Chitosan-Coenzyme Q10 as Bone Graft Materials Covid Pandemic Towards Increased Risk of Stunting. trol of the disease in many countries, including Italy and. Portugal,11 In a recent large survey including almost patients with COPD selected by the.

 
 

Windows 10 1703 download iso italy covid symptoms

 
 

Healthy subjects were selected to ensure the validity of the data, and incomplete questionnaires were excluded. Linear regression and logistic regression were used to analyze the relationship between the environmental parameters and the responses to the subjective questionnaire.

The observations of the measured indoor thermal parameters T a , RH , V a , and T mrt measured are summarized in Table 4. The minimum RH of the air in the library reached The distribution of environmental parameters in the library is shown in Fig. T op in the library was mostly Owing to the influence of solar radiation, the fifth floor of the library showed the highest temperature.

The proportion of indoor V a less than 0. Distribution of indoor environmental parameters in the library: a T op ; b RH ; and c V a. Among the questionnaires collected, questionnaires of subjects who wore masks were included. Among them, The voting distribution for discomfort regarding each body part is shown in Fig. The proportion of facial discomfort was the largest The proportions of head and chest discomfort were Wearing masks for a long time may cause headache, dyspnea, and other symptoms; therefore, the proportions of discomfort due to these two symptoms would increase over time.

Some subjects who wore masks for a long time experienced rapid heartbeat 9. Percentages of participants who voted that they experienced discomfort in various body parts. A greater proportion of subjects with masks preferred a higher air velocity than that of subjects without wearing masks.

Additionally, the more than half subjects preferred reduced the operative temperature to improve thermal comfort, specially the subjects with masks. Thus, effects of masks on thermal comfort are significant.

The demands of air velocity and operative temperature was different between wearing masks and without wearing masks. In addition, most subjects opined that the humidity level was acceptable. The primary reason is that the subjects has strong adaptive ability in high relative humidity in South China [ [54] , [55] , [56] ].

Therefore, in order to improve the thermal comfort in an air-conditioned room, the operative temperature needs to be lower with higher air velocity. Distribution of percent thermal preference for environmental parameters with or without masks. The overall and local TSV results showed that wearing masks has a certain impact on human thermal sensation Fig.

The proportion of subjects wearing masks who reported TSV greater than zero was approximately 6. Considering individual parts of the body, the most obvious change in the TSV was in the face, where the percentage of subjects wearing masks and reporting a TSV greater than zero increased by approximately The proportion of subjects who wore masks and reported a TSV greater than zero for the head and chest were 6.

Further, the proportion of subjects who wore masks and reported a TSV greater than zero for the back and limbs was small. Wearing masks can affect the breathing frequency and inspiratory capacity, thereby resulting in heat accumulation on the face, and an overall feeling of excessive heat.

Percentage distribution and normal distribution curve of thermal sensation votes in the library: a Whole; b Face; c Head; d Back; e Chest; and f Limbs. No difference was observed between those with and without masks in their voting on the feeling of heat and wind on the back, chest, and limbs. The most obvious differences between the subjects who wore and did not wear masks were in their reporting about the face and head. For the whole body MTSV, similar differences were observed between the subjects who wore and did not wear masks.

These correlations were calculated based on thermal sensation voting. The results were reasonable. The small p-value indicates that there is a significant difference between them, which indicates that there is a significant difference between wearing masks and not wearing masks in the whole thermal sensation and some local thermal sensation.

Most subjects always feel acceptable in whole body thermal sensation. In addition, the comfort temperature was determined by the whole body thermal sensation. Thus, the difference of comfort temperature between masks and no masks were not significant.

However, from Figs. Therefore, it is very necessary to control environmental parameters for human local thermal sensation and whole body thermal sensation.

The probability curves are shown in Fig. The preferred T op of the subjects without masks was Many previous investigations also found that the neutral temperature was higher than the preferred temperature [ 25 , [55] , [56] , [57] , [58] , [59] ].

However, in some previous investigations, the preferred temperature is equal to or higher than the neutral temperature [ 60 , 61 ]. For example, Tewari et al. Zheng et al. In addition, some previous investigations show that the regression method were used to analyze the subjects\’ behavioral adaptation [ [62] , [63] , [64] ]. In hot summer and warm zoom, human have strong adaptability of hot thermal environment. In air-conditioned indoor thermal environment, the set temperature always lower than nature ventilation condition.

The subjects were trained in cooler indoor thermal environment. Thus, the neutral comfort temperature was lower than preferred temperature. As shown in Table 5 , the zone of acceptable T op according to PD was Contrastingly, the acceptable temperature zone obtained by PD was In addition, wearing a mask shifted the acceptable temperature and comfort temperature zones to a lower temperature.

The longer the duration for wearing masks, the wetter the face will be, thereby reducing the comfort of the human body. Wearing masks while traveling, and in work and study places has become a daily part of people\’s lives [ 65 ]. The discomfort accompanied by wearing masks has also attracted attention [ [66] , [67] , [68] ]. In the study or work place, wearing a mask for a long time may lead to a certain degree of physical symptoms.

While wearing masks, people need a more comfortable environment to reduce the thermal discomfort caused by masks. Subsequently, people often remove their masks to alleviate their discomfort, which reduces work efficiency [ 68 , 69 ]. The inner layer of a mask that has been worn for a long time gets wet because of condensation of the water vapor generated by breathing and sweat evaporation [ 16 , 68 ]. People usually do not change masks regularly, and continue wearing the same mask for a long time, which affects both hygiene and comfort.

This study found that people who wore masks preferred increased air velocity, especially to alleviate the discomfort on the head and face. The mask, which is in direct contact with the head and face, not only hinders the evaporation and heat dissipation from the head and face but also breathing, which explains the large proportion of chest discomfort.

Therefore, fever and redness on the face and dyspnea were the most prevalent symptoms that were reported after wearing a mask for a long time. According to Fig. To analyze whether the regression equations of MTSV and T op obtained in this study were adaptive, we compared the results of this study with those of previous studies. Table 6 summarizes the relationship between the MTSV and the thermal indices in summer.

Different regression equations were obtained in different places, and the calculated neutral temperatures were also different. In summer, for Guangdong, the neutral temperature of Guangzhou [ 56 , 70 ] differed from that of Shenzhen [ 55 ]. The neutral temperature in Shenzhen was The acceptable temperature range was In this study, the acceptable temperature range was This difference could be possibly because prefabricated site offices are mainly used for construction workers, and their heat resistance is greater than that of people working in regular offices [ 44 , 54 , 55 , [72] , [73] , [74] ].

A study in Shenzhen reported that as people wear more layers of clothes when the ambient temperature is low, which increases their thermal resistance, they adapt to a large temperature range [ 55 ].

Further, wearing masks lowered the neutral temperature value, and the acceptable and comfort temperature ranges shifted to the left. Therefore, the influence of humidity on thermal sensation was not analyzed in this study. In addition, the instrument for measuring environmental parameters was placed at a height 1.

We suggest that when filling in the questionnaire, the subjects only consider that the factor causing their discomfort is wearing masks. Of course, the causes of discomfort also include air quality and environmental parameters, which need to be considered in big data research and need to be paid attention to in future research.

Therefore, we could only make a general comparison based on the existing voting data to analyze the sensitivity of each body part to the thermal environment in the study area. Additionally, we only analyzed the comfort of the Operative temperature as a whole without masks and with masks.

In addition, subjects of different genders also have an impact on the value of thermal indicators [ 75 ]. In this experiment, female subjects are about twice as much as male subjects, so the neutral temperature and comfort temperature may be biased towards female needs. In the summer of , a field test and a questionnaire survey were conducted in a university library in Guangzhou, China. By analyzing the perceived thermal sensations and the thermal index of each parameter under the different environmental conditions for subjects with and without masks, the following results were obtained:.

Tianwei Tang: Writing — original draft, Methodology, Data curation. Yongcheng Zhu: Formal analysis, Data curation. Zhisheng Guo: Investigation. Yudong Mao: Investigation. Huilin Jiang: Resources. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The authors express gratitude to all the subjects who participated in the survey. Build Environ. Published online Feb Author information Article notes Copyright and License information Disclaimer. All rights reserved. Elsevier hereby grants permission to make all its COVIDrelated research that is available on the COVID resource centre – including this research content – immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source.

Literature review Personal medical masks typically consist of three layers with a melt-blown microfiber filter between two layers of spunbond fabric. Research objective In this investigation, the subjects were the students in Guangzhou University library, which is a public place with a high population density.

Determine the impact of wearing masks on the personal comfort of students in Guangzhou University Library. Establish different thermal comfort models under the conditions of wearing masks and not wearing masks. Methods The methods of this study are as follows.

Research environment The study was conducted in the Guangzhou University library Fig. Open in a separate window. Subjective survey and measurements A total of healthy college students males and females; detailed information is provided in Table 1 were randomly invited to participate in the survey. Table 1 Anthropometric data of subjects SD: standard deviation.

Table 2 Subjective vote scale. Table 3 Instruments used to measure the air temperature T a , relative humidity RH , globe temperature T g , air velocity V a.

Data processing Healthy subjects were selected to ensure the validity of the data, and incomplete questionnaires were excluded. Results 3. Thermal parameters The observations of the measured indoor thermal parameters T a , RH , V a , and T mrt measured are summarized in Table 4. Table 4 Indoor thermal parameters. Effect of wearing masks on human comfort Among the questionnaires collected, questionnaires of subjects who wore masks were included. Distribution of the percentage of symptoms among participants wearing masks.

Effect of wearing mask on thermal preference Fig. Distribution of thermal sensation vote The overall and local TSV results showed that wearing masks has a certain impact on human thermal sensation Fig. Box plot for a thermal sensation vote and b air movement sensation vote. Table 5 Unacceptable percentage of Operative temperature under different conditions. Discussion 4. Effect of wearing face masks on human thermal comfort Wearing masks while traveling, and in work and study places has become a daily part of people\’s lives [ 65 ].

Adaptive analysis of the operative temperature To analyze whether the regression equations of MTSV and T op obtained in this study were adaptive, we compared the results of this study with those of previous studies.

Table 6 Comparison of the TSV model with previous studies conducted in offices. This approach removes the dependency of choice of the initial cluster centers as well as the ACSO approach determines the optimal cluster centers by optimizing some validity indices.

These advantages motivate us to apply the proposed approach to automatically segment the radiological images that will be certainly helpful in diagnosing some symptoms of COVID The experimental outcomes show the efficiency of the proposed approach. Under this pandemic environment, this work is designed hoping that it can help physicians and other domain experts to some extent in the early diagnosis of the disease. Early diagnosis can prevent the drastic spread of this highly infectious virus.

Quantitative results do not have any direct implications in real-life diagnosis. The segmented outcomes are useful in the diagnosis process. Physicians can investigate the segmented outcomes to find some prominent and common features as mentioned in Table 2. The segmented images will be helpful in the easy interpretation of the radiological images.

The proposed SUFACSO approach is an efficient image segmentation approach that can effectively segment the radiological images that highly useful in the easy interpretation of these images. There is a high possibility that a suspected patient can spread the disease in the community completely unwillingly.

The proposed approach can reduce this chance because an initial screening can be performed by the physicians comfortable with the help of the proposed SUFACSO approach. It is worth mentioning here that the proposed approach is neither a replacement of the RT-PCR test nor it can confirm the presence of the virus accurately. However, this approach can be helpful in an initial screening at an early stage that will restrict the spread of this highly infectious virus by separating suspected patients from the rest of the community.

The obtained results indicate that the proposed approach is suitable for real-life scenarios and also performs efficiently. This approach can be easily adapted for the automated screening purposes of the COVID infected patients.

It is assumed the quality of the CT scan images is considerably high and the performance of the proposed approach is not verified against the presence of noise. It will be interesting to study the proposed approach in the presence of noise. The scalability of the proposed approach to different types of biomedical images can be explored in future studies.

Missing manual annotations can jeopardize the generalizability of the proposed work. On the other hand, the obtained results are quite promising and encouraging. From the best of the knowledge of the authors, there is no publicly available manually annotated dataset for the chest CT scan images of the COVID positive cases. Although the proposed approach is efficient enough to segment the CT scan images automatically and produces realistic segmented outcomes still, some important drawbacks can be observed in this proposed approach that can be addressed in the subsequent works.

One important drawback of the proposed approach is that it cannot automatically determine the number of clusters and it can be overcome in future works.

Automated estimation of the clusters can make this approach more realistic, robust, and application friendly. The proposed method can handle only a single objective at a time. Therefore, the proposed approach is not suitable for multi-objective optimization issues unless enhanced further. The number of images in the dataset is not very large. So, the proposed approach can also be tested on some additional CT images of COVID infection as well as on some standard dataset of the biomedical images.

It neither use any training dataset nor uses any pre-trained model. The proposed approach can effectively segment the radiological images that are collected from different patients i. It is to be clarified that this approach cannot take any decision about the type of disease automatically. For example, the proposed approach cannot automatically differentiate between COVID related lung images and other lung diseases.

This approach aims to help physicians in early and quick interpretation of the radiological images and diagnosis of the diseases without any manual delineations. This article proposes a novel, simple and elegant solution that uses some of the important features of the chest CT scan images to screen the COVID suspected patients easily and at an early phase which can be considered as an effective tool to reduce the drastic spread of this virus. From Fig.

Both qualitative and quantitative study produces some satisfactory results which help to make the proposed approach trustworthy so that it can be reliably adapted in the real-world scenarios. The proposed approach initially performs a superpixel-based clustering using the proposed superpixel computation method which significantly reduces the computational overhead for the further clustering process by reducing a large amount of spatial information.

Therefore, radiological images can be conveniently explicated with the application of the proposed method and the proposed approach is also helpful in the easy interpretation of the radiological images. The proposed work neither claims that the suggested approach is cent percent accurate in determining the COVID infection nor claims that it can be a replacement of the RT-PCR test but, the proposed method can help detect some common characteristics from the CT scan images, that can help to isolate some suspected patients from the rest of the community.

The proposed approach is helpful for the early screening of the COVID besides being a significant contribution to the image segmentation literature. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The authors would like to express their gratitude and thank the editors, anonymous reviewers, and referees for their valuable comments and suggestions which are helpful in further improvement of this research work. The dedicated graphics memory is not utilized for any kind of processing purposes.

The system in which the experiments are carried out is equipped with the Microsoft Windows 7 64 bit operating system. It is not at all essential to use the Matlab environment to implement the proposed approach.

We have chosen Matlab due to the availability of some inbuilt functions which are helpful to reduce the coding complexity. Still, any other languages or platforms can be used to implement the same. It is assumed that there are no manual annotations available and the proposed approach is capable to process the images without having any prior knowledge. The final segmented images are constructed by assigning the superpixel to their corresponding cluster centers.

These segmented images are helpful to interpret different features from these radiological images. Appl Soft Comput. Published online Feb 3. Author information Article notes Copyright and License information Disclaimer. All rights reserved. Elsevier hereby grants permission to make all its COVIDrelated research that is available on the COVID resource centre – including this research content – immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source.

Abstract Due to the absence of any specialized drugs, the novel coronavirus disease or COVID is one of the biggest threats to mankind Although the RT-PCR test is the gold standard to confirm the presence of this virus, some radiological investigations find some important features from the CT scans of the chest region, which are helpful to identify the suspected COVID patients.

Introduction Automated computer-aided systems prove their effectiveness and real-life applicability in various scenarios. Table 1 Some of the related literatures and their brief overview.

The calibrated source-to-background curves are used to determine the volume using the iterative thresholding procedure. One major drawback of the system is that it cannot effectively measure small volumes. Wiemker et. This work proposes a divergence theorem and histogram-based Ct image segmentation approach.

This approach is can effectively and optimally isolate the lung nodules from the CT scan images. In this context, the optimality is defined in terms of the mean gradient of the iso-surface and the sphericity. Asari et. This algorithm is consisting of two stages where the first stage employs a global thresholding approach and in the second phase, the differential region growing is used to extract the gastrointestinal lumen from the endoscopic images.

The dynamic hill-clustering approach is used to ascertain the effectiveness of the termination criteria and to look after the growth process. Yu-qian et. Traditional gradient-based edge detection approaches are susceptible to noise and therefore, this approach proposes a novel approach to detect edges of the lung CT scan images using mathematical morphology.

This approach is tested on the CT images which are corrupted with the salt-and-pepper noise and its efficiency is proved by comparing this approach with some of the other standard approaches. It is observed that this approach can efficiently reduce the effect of noise and also can generate precise edges.

Falcao et. This approach is highly dependent on the user intervention to efficiently determine the segmented regions and to define the objects.

This approach is found to be 3 to 15 times faster compared to manual tracing. This approach can be applied almost independently to the applications. One main problem associated with this method is the difficulties associated with the choice of slabs and orthogonal slices which has a serious impact on the efficiency of this approach.

Pan et. The proposed approach addresses the problem of discontinuous edges and dependency on the initialization which are associated with the traditional edge detection approaches. In this work, the intensity of the gradient images is modeled as the concentration of the nutrients and the property of the bacteria Escherichia coli. The edges are highlighted as the paths of the bacteria. Although this approach performs well and comparative study shows the effectiveness of the proposed approach still, one problem of this approach is not very robust to noise.

Noise can lead to crumpled edges. This approach is not also suitable to handle overlapped cells. Ji et. Traditional fuzzy C-means clustering approach does not consider the spatial information and less robust to noise. This work proposes a modification which is known as the weighted image patch-based FCM. In this work, pixels are replaced with the weighted patches which is helpful to incorporate spatial information in the segmentation process. It is helpful to increase the reliability of the overall segmentation process but it also increases the computational overhead drastically.

Agrawal et. This work proposes a novel hybrid approach which is based on the genetic algorithm and the bacterial foraging algorithm. The combination of these two approaches is used to optimize the objective function of the fuzzy c-means clustering.

The final cluster centers are obtained using a method called optimum boundary point detection. This approach cannot determine the optimal number of clusters automatically and produces inaccurate results if the predefined clusters and the actual number of clusters differ.

This approach is based on intuitionistic fuzzy set theory and it is known as the intuitionistic fuzzy C means clustering. In this work, a novel objective function which is known as intuitionistic fuzzy entropy is incorporated with the traditional fuzzy C-means clustering.

This approach is applied to different CT scan images to prove its efficiency. Miao et. This approach can be divided into two phases where the first phase incorporates a dictionary learning method to handle the noise.

In the second phase, this dictionary learning approach is hybridized with the Improved fuzzy c-means clustering approach. The proposed approach is not efficient for medical images with inhomogeneous intensity distribution.

Open in a separate window. A brief overview of the artificial cell swarm optimization procedure This is a recently developed metaheuristic procedure that is inspired by the artificial cell division procedure. The incorporated modifications are listed below [47] : i. The artificial cells are not depending on the current state to participate in the cell division process. Fuzzy C-means clustering based on type 2 fuzzy system The proposed approach adopts the type 2 fuzzy logic-based clustering approach to effectively model and handle the random uncertainties.

A point with higher uncertainty has a lesser impact on the overall clustering process and vice-versa. It helps to achieve more realistic results. Proposed method of superpixel computation The ever-growing technology allows us to increase the quality of the image acquisition hardware. Table 3 Details of the CT scan images under test. Proposed superpixel coupled fuzzy ACSO approach-based segmentation The conventional fuzzy C-means clustering approach often overlooks some important spatial information that can be costly in terms of the segmentation performance.

Dataset description CT scan images of the chest region are collected from the COVID positive patients from different geographic regions. Experimental results The experiments are performed in the MatLab Ra on a computer that is equipped with an Intel i3 processor and 4 GB main memory.

Table 4 Performance evaluation of different approaches using Davies—Bouldin index The highlighted values indicates acceptable values. Image Id Algorithm No. Table 5 Performance evaluation of different approaches using Xie—Beni index The highlighted values indicates acceptable values.

Table 6 Performance evaluation of different approaches using Dunn index The highlighted values indicates acceptable values. Table 8 Comparison of the proposed approach with the active contour method. Study of the convergence rate The rate of convergence is an important parameter to be studied. Analysis of the complexity The time complexity is an important aspect that is to be analyzed.

Discussion 6. Threats to validity The obtained results indicate that the proposed approach is suitable for real-life scenarios and also performs efficiently. Limitations Although the proposed approach is efficient enough to segment the CT scan images automatically and produces realistic segmented outcomes still, some important drawbacks can be observed in this proposed approach that can be addressed in the subsequent works.

Conclusion This article proposes a novel, simple and elegant solution that uses some of the important features of the chest CT scan images to screen the COVID suspected patients easily and at an early phase which can be considered as an effective tool to reduce the drastic spread of this virus.

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments The authors would like to express their gratitude and thank the editors, anonymous reviewers, and referees for their valuable comments and suggestions which are helpful in further improvement of this research work.

Software setup The system in which the experiments are carried out is equipped with the Microsoft Windows 7 64 bit operating system. References 1. Kim T. Learning full pairwise affinities for spectral segmentation. IEEE Trans.

Pattern Anal. Chakraborty S. In: Chakraborty S. IGI Global; An overview of biomedical image analysis from the deep learning perspective. Object Recognit. Motion Detect. Video Process. A study on different edge detection techniques in digital image processing; pp.

Libbrecht M. Machine learning applications in genetics and genomics. Tang C. IEEE Int. BIBE Interrelated two-way clustering: An unsupervised approach for gene expression data analysis; pp. In: Appl. IGI GLobal; An advanced approach to detect edges of digital images for image segmentation. Expert Syst. Multi-Objective Optim. Springer Singapore; Singapore: Application of multiobjective optimization techniques in biomedical image segmentation—A study; pp.

Springer; An optimized intelligent dermatologic disease classification framework based on IoT; pp. Hore S. Specifically, the regional analytical datasets regarding incident patients underwent to kidney transplant in the years —19 were created using an open-source tool for distributed analysis.

Results: Overall, 3, kidney recipients were considered, of which During a median follow-up period of 4. Among safety outcomes, serious infections had the highest incidence 9. Conclusion: In clinical practice, a significantly better benefit profile has been demonstrated for kidney recipients treated with TAC compared to CsA. In particular, the combination of TAC and mTOR appears to be the optimal strategy reducing the incidence of severe infections. Our findings on long term risk-benefit profile of immunosuppressive therapy may be helpful to define the optimal drug therapy in kidney recipients.

Comparison of tacrolimus and cyclosporine for immunosuppression after renal transplantation: An updated systematic review and meta-analysis.

Saudi J Kidney Dis Transpl. Target of rapamycin inhibitors TOR-I; sirolimus and everolimus for primary immunosuppression in kidney transplant recipients. Cochrane Database Syst Rev. Timing of mTORI usage and outcomes in kidney transplant recipients. Int J Med Sci. Published Jan 9. Due to the small sample size of pivotal trials in pediatrics, real-world evidence on the safety of those vaccines in the pediatric population is urgently required. Objective: i To investigate the safety of COVID vaccines by measuring frequencies of solicited and serious adverse events following immunization AEFIs with the first and the second doses of vaccines through active surveillance and, ii to compare the results with the published clinicaltrials in children and adolescents.

Of them, only Overall, Conclusion: This study confirmed safety profile of COVID vaccines in the pediatric population as already documented in the pivotal trials, with a high frequency of local solicited adverse events and an extremely low rate of serious adverse events.

Introduction: Advances in the treatment of cancer in young patients have led to great improvements in life expectancy. However, treatment with chemo or radiotherapy causes reduction of sperm counts often to azoospermic levels that may persist for several years or be permanent.

Oligospermia or azoospermia and long-lasting testicular atrophy are common adverse consequences of cancer treatment 1. Cases of oligospermia and azoospermia were identified using MedDRA v No Dis-Rep was found for any of the 14 AA TKIs: acalabrutinib, axitinib, cabozantinib, dacomitinib, lenvatinib, neratinib, nintedanib, pazopanib, ponatinib, regorafenib, sorafenib, sunitinib, tivozanib and vandetanib.

The analysis in VigiBase database yielded similar results. Our results however, should be interpreted with caution as disproportionality analyses are hypothesis generating rather than hypothesis testing. Meistrich, M. Clinical drug investigation. Bate A, Evans S. Quantitative signal detection using spontaneous ADR reporting.

A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Skin lightening products contain high concentrations of harmful ingredients such as hydroquinone, mercurials, and corticosteroids, and are reported to cause serious complications such as hyperpigmentation, exogenous ochronosis, wound dehiscence, nephropathy, steroid addiction syndrome, predisposition to infections, and other endocrinologic complications.

Despite all these public health risks, they have been used in many countries without regulation and consultation of healthcare professionals 3. Similarly, in Eritrea, there is uncontrolled marketing and use of SLAs even those with banned harmful ingredients. Objective: This study was conducted to assess the perception and utilization of SLAs among females of Asmara, the capital city of Eritrea. Methods: A cross-sectional descriptive study was conducted in representative samples of all beauty salons available in Asmara between May and July The study participants were selected using two-stage stratified cluster sampling technique.

The data collected through face-to-face interview was entered and analyzed using CSPro 7. Results: The study enrolled females. The majority of the respondents agreed that SLAs can make someone white About two-third Of those who ever used SLAs, About half of the respondents With the use of SLAs, Employed females AOR: 1. Conclusion: Utilization of SLAs among females was prevalent. They were satisfied with its use despite experiencing adverse effects which urges coordinated efforts in tightening the regulation of cosmetics in general and establishment of cosmetovigilance systems in particular.

Widespread use of toxic skin lightening compounds: medical and psychosocial aspects. Dermatologic Clinics, Afr Health Sci. The global prevalence and correlates of skin bleaching: a meta-analysis and meta-regression analysis.

Int J Dermatol. Introduction: Drug therapy in paediatrics is often associated with uncertainties due to lack of data from clinical trials. Due to this off-label use, missing paediatric dosage forms and complex dose calculations, medication errors ME occur up to three times more frequently compared to adults [3].

Objective: The aim of the study was to investigate the nature, characteristics and preventability of drug-related hospital admissions in paediatrics.

If parents had given consent for data transfer and further analysis, the suspected ADRs resp. MEs were subsequently validated by a blinded, independent expert team [6]. All ADRs and MEs were assessed with regard to their nature, preventability, severity and drug association. Results: Of Consent for further analysis was obtained for 9. Allergic conditions, seizures incl. Treatment noncompliance, accidental exposure to product and dosing problems mainly underdosing were primarily identified as MEs in connection with the use of antiepileptic drugs, insulins and analogues and other beta-lactam-antibacterials.

Conclusion: Drug-related hospital admissions play a significant role in paediatrics. Moreover, almost half of them are considered preventable and therefore result in unnecessary harm and treatment costs. Dosing databases, training, and systematic screening for ADRs and MEs have great potential to increase the safety of drug therapy in children.

Kimland, E. Odlind, Off-label drug use in pediatric patients. Clin Pharmacol Ther, Magalhaes, J. Eur J Clin Pharmacol, Kaushal, R. JAMA, Smyth, R. PLoS One, Gallagher, R. Schulze, C. J Patient Saf, The lack of staff trained in PV is one of the most serious limiting factors affecting the development of PV in resource-constrained settings. Previous experiences suggest that blending learning programmes can be implemented in resource-limited countries to train health care professionals HCP with remarkable gains in terms of knowledge acquisition.

Methods: We developed the blended-courses integrated with a Train of Trainers scheme [1]. Two e-learning courses were made available on a web-based application, together with a manual on how to combine the e-learning courses together with face-to-face interactions. The blended course were given in Tanzania, Eswatini and Nigeria. Results: In the three countries 95 participants were trained Table 1. All participants completed the two courses and the mean score of the post-test was significantly greater than on the pre-test Table 1.

In the second level, the participants from the first training were training others. The majority of respondents to questionnaires have been satisfied, declared they felt more involved in PV and reported at least an ADR after the training both in the first and second level. The trends of reporting increased in the twelve months after the training if compared to the previous twelve months: vs and vs ICSRs were reported to Vigibase for Tanzania and Eswatini National Agency respectively.

Conclusion: Our results demonstrated that a blended course can reach an important number of participants and improve their knowledge. It is difficult to establish how much of the increase of reports was attributed to the blended learning training. Alammary A. Blended learning models for introductory programming courses: a systematic review. Plos one. The views and opinions of authors expressed herein do not necessarily state or reflect those of EDCTP.

Introduction: Considering data from the literature in favor of active educational intervention to teach pharmacovigilance, we describe an innovative model of distance learning clinical reasoning sessions CRS of pharmacovigilance with 3rd year medical French students.

Objective: The three main objectives were to identify the elements necessary for the diagnosis of an adverse drug reaction, report an adverse drug reaction and perform drug causality assessment. Methods: The training was organized in 3 stages. First, students practiced clinical reasoning CRS by conducting fictive pharmacovigilance telehealth consultations.

Second, students wrote a medical letter summarizing the telehealth consultation and analyzing the drug causality assessment. This letter was sent to the teacher for a graded evaluation. In the third stage was a debriefing course with all the students.

Results: Of the third-year medical students enrolled in this course, participated in the distance learning CRS. The evaluation received feedback from students, with an average score of 8. The qualitative evaluation had only positive feedback. The students appreciated the different format of the teaching, with the possibility to be active. Conclusion: Through distance CRS of pharmacovigilance, medical students\’ competences to identify and report adverse drug reactions were tested.

The students experienced the pharmacovigilance skills necessary to detect adverse drug reactions in a manner directly relevant to patient care. The overall evaluation of the students is in favor of this type of method. Methods: This research used a qualitative inductive methodology through thematic analysis. The first step was to identify, through a literature review, current practices for herbal pharmacovigilance. Based on the findings a semi-structured interview guide was designed, and purposive sampling was used to recruit the interview participants.

By using a snowballing technique more potential participants were reached. Most of these recommendations are applicable worldwide, while some are limited to certain regions.

Tong, A. Consolidated criteria for reporting qualitative research COREQ : a item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19 6 , — Introduction: Although medical cannabis MC has been available in Canada since , lack of recognition of MC as a drug has restricted patient access. The Quebec College of Physicians, between and , authorized MC use only within a research framework. Follow-up ended due to either MC discontinuation, loss to follow-up, 3 years follow-up, or end of data collection May , 6 months after the last patient in.

Data were collected at inclusion and at follow-up visits every 3 months for the first 2 years, then at least once per year in the third year. MC mode of administration ingestion, inhalation, other , and cannabinoid content ratio tetrahydrocannabinol THC -dominant, cannabidiol CBD -dominant, or balanced were documented.

Results: 2, patients were enrolled in the registry mean age Over follow-up, 3. Reports included a total of AEs average 1. The most common PTs were dizziness Conclusion: There were no new safety concerns identified in the Registry, although notable differences in AE profile between modes of administration and cannabinoid content ratios should be considered by health professionals. Further work identifying and managing risk factors for AEs is warranted to maintain a favorable risk-benefit ratio for MC.

Introduction: Dengue is one of top ten global health threats and is a serious burden in the Philippines. Dengvaxia immunization program was launched on April for children 9—year-olds in three regions with high statistics of dengue, hospitalization, and deaths. This was coincidentally the campaign period for national elections. Use of vaccine, once available, was part of a strategy to control epidemic. Current measures were inadequate. What started as vaccine-vigilance information sparked a public outcry.

This led to a series of parliamentary investigations, traditional and social media misinformation and disinformation vilifying the health decision makers and the company, and criminal charges filed against over 20 individuals by the state over alleged unproven vaccine caused deaths. Despite attempts to correct these narratives by a few health professionals, the damage to institution, the program, the product, and individuals have been done.

The consequences of such actions of emotional approach without understanding the science have resulted in creating general vaccine rejection, hesitancy, other outbreaks such as measles, lowered confidence even with recent COVID vaccines.

Objective: This abstract aim to describe the situation at that time in the Philippines and extract lessons that will inform better risk communications during crisis. Results: Some of the important lessons learned are in risk management and communications.

Adverse health product information should be announced with circumspect considering the level of health literacy and risk appreciation in a country. Partisan politics interfered with poorly understood science, fueled by imprudent comments by officials and health professionals who spoke out of turn, amplified by the media and created chaos.

The fear was so palpable that enlightened health professionals refused to provide countervailing facts. Reinstating the vaccine would be perceived as the government had back-pedaled on a mistake. In the meantime, the drama contributed to vaccination hesitancy and outbreaks.

Conclusion: Public health decisions are policy and regulatory decisions anchored in ethical and utilitarian principles. Edillo et al. Economic Cost and Burden of Dengue in the Philippines.

Vannice, et al Mendoza, Dayrit, Valenzuela. Dengue researcher faces charges in vaccine fiasco. Lasco et. Medical populism and immunisation programmes: Illustrative examples and consequences for public health. Trolleyology and the Dengue Vaccine Dilemma. Dayrit, Mendoza, Valenzuela The importance of effective risk communication and transparency: lessons from the dengue vaccine controversy in the Philippines.

Dengue vaccination: a more balanced approach is needed. Introduction: Vaccines are vital tools to control epidemic and pandemic diseases, such as COVID, demonstrating safety and effectiveness.

However, rare adverse events of special interest AESIs following vaccination arise with every new emerging pathogen vaccine program. Adversomics, a set of technologies that measure the inventory of molecules e. The International Network of Special Immunization Services INSIS brings together vaccine safety, public health, and systems biology experts in middle- and high-income countries to investigate the causes of, and identify strategies to mitigate AESIs following vaccination insisvaccine.

Brighton Collaboration case definitions and harmonized protocols will be employed to collect detailed clinical data and serial blood samples suitable for adversomics e. Integration of clinical and biological data will enable comparisons of analyte levels and immune responses within groups over time and between cases and controls. Global collaboration across five continents will ensure adequate sample size. Conclusion: INSIS-led studies will provide insight into pathways triggered in these AESIs and susceptible populations to inform vaccine development strategies to reduce the potential to trigger pathways involved in AESIs, risk-benefit assessment, and personalized vaccination strategies.

Introduction: During the covid 19 period, several countries needed to set up or develop their pharmacovigilance systems, unfortunately containment and the closure of borders prevented the organisation of classic training sessions. Objective: The objective of this work is to present the pharmacovigilance simulation game developed by CAPM, RCC and the results of its pilot use with pharmacovigilants from 10 French-speaking African countries.

The game is based on good practices in Pharmacovigilance PV , and inspired by the different WHO guidelines, the experience of the Moroccan PV center, and behaviors consensually considered as the norm in PV. In fact, they are put in a real-life situation to choose actions and strategies for the development of a PV center and must be able to optimize the human and material resources at their disposal to make their center shine within their national health system but also at the level of the international PV network.

Better understand the challenges and outlooks linked to the creation and management of a PV center. Put into practice the theoretical concepts in causality assessment, signal detection and risk minimization actions. During the game, within 10 levels, participants have to set up a PV center following WHO pharmacovigilance indicators: a practical manual for the assessment of pharmacovigilance systems as structural indicators, process indicators and outcome indicators, and following the pharmacovigilance process from collecting data, analyzing them, detecting signals, and setting up national technical pharmacovigilance committee to discuss about safety signals and risk minimization actions to put in place.

Conclusion: The use of the game by the pharmacovigilantes during the pilot phase gave good feedback on the ease of use and the effectiveness of the game in capacity building in pharmacovigilance.

University of Huddersfield, Huddersfield, pp. Introduction: Pharmacovigilance has traditionally been a reactive science with a significant dependence on spontaneous adverse event reporting.

The pandemic on the other hand has accelerated application of novel technologies and approaches to engaging with the patient, remote connected care at their home and dependence on technologies to supplement regular communication channels.

Telemedicine is evolving rapidly and playing a key role in clinical interventions. Objective: Digital Health and novel technologies offer a significant opportunity to enhance pharmacovigilance thru proactive patient monitoring, risk communication, personalized care plans and access to real world data. Leveraging such approaches will not only lead to early detection of risks but also to personalized interventions and improved patient outcomes. Educational material which is more interactive, visual and multi-dimensional can replace paper or text based risk communication material.

This could provide early signal detection in individual patients and enable proactive patient level pharmacovigilance. Educational and risk related material can be dynamically updated based on patient preferences, interactions and profiles. Machine learning approaches which link material with outcome can enhance impact of pharmacovigilance methods and tools.

In order to utilize the full potential of such options it is critical that the regulatory framework is updated to enable such approaches which complement traditional PV and can drive efficiencies and higher effectiveness in the risk communication process. Collaboration within the network of industry and regulators is essential to further such research and maximize the impact on value for patients, HCPs and sponsors. Introduction: Large amounts of data associated with safety issues are generated along the entire lifetime of drugs, from its infancy as preclinical leads, through its adolescence as clinical candidates, all the way up to its adulthood as marketed drugs exposed to the human population.

Across the different stages in the life of a drug, some of the data collected initially may be confirmed and consolidated with data at an advanced stage, whereas other data may not be translated, and in some cases may even contradict, those safety signals that are ultimately observed in the human population. Collecting and properly integrating such an heterogenous pool of data is a complex and tedious task. But even if one manages to put all data together, the construction of useful models to anticipate and detect drug safety signals remains a challenge.

Objective: The presentation will cover our efforts to connect data from in vitro safety pharmacology, preclinical toxicology, clinical safety and post-marketing spontaneous reports for over 9, small molecule drugs, combination drugs, and biologics. A novel consensus approach using various statistical and machine learning methods to anticipate side effects of potential safety concern, detect adverse drug reaction signals and perform pharmacovigilance analyses will be introduced.

Use case application examples to individual drugs and drug classes will be discussed. Methods: Our consensus approach to post-marketing surveillance integrates four different methodologies based on detection of prior safety markers, identification of class reactions, statistical projection of disproportionalities based on reporting frequencies and velocities, and machine learning models of translational safety data.

Results: Results on the validation of our approach to anticipating adverse drug reactions of safety concern to the population at the postmarketing stage based on i in vitro safety pharmacology data, ii preclinical toxicology data, iii clinical safety data and iv the first sample of 25 postmarketing spontaneous reports will be presented.

Based on data available in each case, the performance of the different methods varies for different drugs, drug classes, and side effects. A discussion on performances in selected use cases will be included. As an example, the analysis of long-term PARP inhibition on circadian patterns and its dependence on the reporting bias by consumers will be discussed.

Conclusion: Integration and modelling of the large amount of translational safety data currently available from all phases of drug discovery, development and post-marketing to anticipate and follow adverse drug reactions opens an avenue to a whole new perspective in pharmacovigilance.

Introduction: Psychedelics are unique psychoactive chemicals that can change consciousness by acting on 5-HT2A receptors []. There is limited knowledge concerning the online interest in psychedelics that we can extrapolate via trends websites. Objective: We aim to examine the online information-seeking behavior concerning the most popular psychedelics, including cannabis—a quasi-psychedelic—in the European Union EU members of interest and the UK before and during the pandemic.

Methods: We designed a \”dictionary\” of terms to extract online search data from Google Trends concerning psychedelics and cannabis from Jan to 1-Jan We conducted a triple Holt-Winters exponential smoothing—additive model—for time series analysis to infer seasonality [4, 5]. We utilized hierarchical clustering—an unsupervised machine learning method—to explore clusters of countries concerning the spatial geographic mapping of these chemicals.

We also implemented—a t-test—for comparing the slope difference of two trends before versus during the pandemic. Results: There was an evident seasonal pattern for cannabis, NBOMe, and psilocybin in almost all nations of interest.

Similar patterns existed in France and the UK, while those in Germany, Sweden, and Romania had relatively shorter periodicity. Analysis of slopes and hierarchical clustering conveyed differentiated patterns concerning the temporal and spatial mapping, respectively, while contrasting the two periods before versus during the pandemic.

Conclusion: Cannabis and psychedelics follow somewhat a consistent pattern concerning seasonality across Europe; some correlate with the seasonal harvesting of mushrooms, and others with public holidays, including Christmas, the new year holiday, or school breaks. The pandemic influenced some significant changes concerning the online interest in the EU and the UK; nonetheless, we should rely on more rigorous longitudinal and experimental study designs—possessing a superior level of evidence—to confirm the causal relationship.

However, these patterns might be insightful for decision-makers and regulatory authorities—like the EMCDDA—to prognosticate and prevent addiction catastrophes. Understanding and using time series analyses in addiction research. Carhart-Harris RL. How do psychedelics work?. Current Opinion in Psychiatry. Novel psychoactive substances: types, mechanisms of action, and effects.

British Medical Journal. Robust forecasting with exponential and Holt—Winters smoothing. Journal of Forecasting. Gardner Jr ES. Exponential smoothing: The state of the art—Part II.

International Journal of Forecasting. Introduction: Continuous monitoring of the safety profile of drugs is one of the critical processes of pharmacovigilance. As medical literature might be valuable source of safety data, especially for rare, unlisted, serious cases, all MAHs are obliged to medical literature monitoring MLM in all marketing countries [1].

This approach can be changed through modern automation techniques. Objective: To develop and test a tool for automated monitoring of local literature and enhance drug safety data identification. Methods: Modern programming approaches were used to create PV platform, intended for automated literature screening. GAMP 5 recommendations were used to prove the validation status.

Results: We developed a tool—DrugCard PV platform which screens local medical sources for updates on a weekly basis. Till May we added around local journals originated from 10 countries that cover different therapeutic areas.

Our tool automatically searches for defined keywords drug trade names, active substances in published articles. Different file formats can be screened including text, pdfs, images etc. In case a new issue of a journal is published—a PV specialist will receive an email notification. The mandatory features of a validated computerized system, like audit trail, logs, reports are also present here.

Instead of manual reading of the whole journal issue the user only should read a separate article, analyze whether there is a valuable safety data and label it depending on the content. PV specialists may work together inside the platform and provide a quality check for labeled articles. Our pilot study of how a new tool may improve the efficiency revealed interesting results. Despite the dramatically decreased amount of time needed, the number of identified ICRSs from literature increased.

During the abovementioned pilot study of automated local literature monitoring lasting 2 months, 31 safety cases were identified valid and non-valid ICSRs. This is much more than usual rate of safety cases finding. It offers increasing efficiency in safety information identification with less time spent on routine activities. Certificate of copyright in Ukraine. Hyperacute toxicity is a recent newly described entity, albeit incompletely characterized [3].

We selected reports with available information to calculate a plausible time-to-onset. Events of interest were classified into fulminant within 7 days and hyper-acute cases within 21 days, i. Cases were described in terms of demographic and clinical features: age, gender, anticancer regimen combination vs monotherapy , therapeutic indications, seriousness hospitalization , case fatality rate CFR, namely the proportion of cases where death was reported as outcome , co-reported symptoms, co-reported irAEs.

The Immune-Adversome was estimated considering events as nodes and co-reporting as links. Hyperacute cases 18, represented Monotherapy was reported in the majority of cases Pyrexia, diarrhea, fatigue, dyspnea were the most frequently reported symptoms. Hyperacute myocarditis was reported in Among fulminant cases, most frequent irAEs were interstitial lung disease , colitis , hypothyroidism , and myocarditis Other co-occurring irAEs were colitis-hepatitis-thyroiditis, and arthritis and psoriasis.

Our network approach may complement traditional disproportionality analyses in pharmacovigilance for a more effective signal detection technique, thus supporting regulatory and clinical monitoring, especially in complex scenario such as oncology.

Target Oncol ; — Oncologist ; — Hyperacute toxicity with combination ipilimumab and anti-PD1 immunotherapy. Eur J Cancer ; — Introduction: The prolongation of the QT interval is a serious and potentially fatal adverse reaction that has led to the discontinuation of many drugs including some opioids. Data mining on pharmacovigilance databases can detect signals that identify early the risk associated with some drugs.

Results: A total of drug-reaction pairs was found in opioid reports. Analysis of individual opioids show significant signals for QT prolongation for each drug. The temporal evolution of the different signals according to the number of reports included from to shows early significant positivization of signals in the first 6 to 12 months. Underlying mechanism is unknown, but it seems to be linked to hERG channel blocking.

We propose the evaluation of the trend of change in the confidence intervals of the disproportionality parameters as a measure that can predict the occurrence of clinical events at the population level and a posible usefull strategy to minimize adverse reactions. Introduction: Language and speech are increasingly debated as potential markers for diagnosing and monitoring patients with affective and psychotic disorders 1—3. However, many neglected factors may confound communicative atypicalities.

A comprehensive list of potential confounding drugs will support the design of robust communicative marker studies. Objective: We aim at identifying a list of drugs potentially associated with speech and language disorders, within psychotic and affective disorders.

Within the FAERS, we considered separately 3 populations psychotic, affective and non-neuropsychiatric disorders , to account for the confounding role of different underlying conditions. Robustness analyses were performed to account for the biases.

Results: We identified a list of potential expected and 91 unexpected confounding medications for the identification of communication markers of affective and psychotic disorders e.

We developed also a MedDRA query proposal for speech and language conditions, formalization of possible biases, and related analyses to account for them.

Conclusion: We provided a list of medications to be accounted for in future studies of communicative bio-behavioral markers in affective and psychotic disorders. The methodological procedure we developed does not simply facilitate future investigations of communicative biomarkers in other conditions, more crucially it provides a case-study in more rigorous procedures for digital phenotyping in general.

Insel TR. Automated assessment of psychiatric disorders using speech: A systematic review. Laryngoscope Investigative Otolaryngology. Voice patterns in schizophrenia: A systematic review and Bayesian meta-analysis. Schizophr Res. Introduction: The comparison of safety profiles for products recently on the market is difficult.

There is a lack of methodology for quantifying the potential differences between products that have the same indication. Objective: Provide the tools to quantify the differences in spontaneous reporting between two products.

An Euclidian distance from the EBGM to the diagonal line measures the deviation from what would have been expected under the null assumption of similar safety profiles. As the deviation does not capture the statistical uncertainty around the estimate, we propose as measure of the deviation the minimal distance of the four Euclidian distances calculated from each of the credibility intervals around the EBGM post Product A and Product B.

A visualization capturing the global trend of the most substantial differences in reporting was generated. Conclusion: This relatively simple method can provide quantification of the differences in reporting and could help prioritize one product over the other for some population subgroups.

Introduction: The application of text mining approaches to identify adverse events AEs from electronic health records EHRs is a growing area of interest in pharmacovigilance research. In veterinary medicine, the majority of EHRs consist of unstructured clinical narratives, hence the development of appropriate methods for identifying AEs of interest is an important step in the research process. Identifying renal disease poses a specific challenge as the event may be described in narrative form or implied by reported test results or the use of renal disease specific medications.

In this study we developed regular expressions regexes to identify relevant mentions of renal disease in veterinary free text clinical narratives. Objective: To develop a method for identifying veterinary patients with renal disease in free text clinical narratives.