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Samira Daniali, Nosrat Riahi,
Volume 14, Issue 4 (10-2020)
Volume 14, Issue 4 (10-2020)
Abstract
Background and Aim: The purpose of the present study is to map the coronavirus domain citation network to better understand this domain based on all other citation networks.
Materials and Methods: The present study is applied in terms of purpose, and is descriptive scientometrics in terms of type, which has been done with the all-citation method. In this study, all scientific publications on coronavirus(6980 documents) in the period 1985-2019 AD were studied on April 10, 2020 in the Web of Science database. For analysis and drawing all citation maps, VOSviewer and Excel software were used.
Results: In the field of coronavirus, 6815 documents, 10246 journals, and 40298 authors were identified. Ksiazek(2003) with the acute respiratory syndrome(SARS) topic received 875 citations and won the first place. The most cited documents in the field of coronavirus have 5 clusters; and the first cluster with 201 documents and with the topic of studying the structure of coronavirus is the largest one. Journal of Virology -- with the thematic range of genome structure and replication, virus identification, etc. -- ranked first with 35,383 citations. The most cited journals in the field of coronavirus are 5 thematic clusters, and the first one is the largest cluster with 121 journals and with the thematic domains of health policy, coronavirus, etc. Also, Woo won PCY first place with his specialization in identifying new microbes and emerging infectious diseases, and receiving 1491 citations. The most cited authors in the field of corona virus are in 6 thematic clusters; the first cluster with 195 authors in specialized field of virology and coronavirus is the largest cluster.
Conclusion: By identifying the highly cited scientific products in the field of coronavirus, efforts have been made to provide a comprehensive view of top documents, top journals, and top authors so that it can be a decision-making tool in the shortest possible time.
Materials and Methods: The present study is applied in terms of purpose, and is descriptive scientometrics in terms of type, which has been done with the all-citation method. In this study, all scientific publications on coronavirus(6980 documents) in the period 1985-2019 AD were studied on April 10, 2020 in the Web of Science database. For analysis and drawing all citation maps, VOSviewer and Excel software were used.
Results: In the field of coronavirus, 6815 documents, 10246 journals, and 40298 authors were identified. Ksiazek(2003) with the acute respiratory syndrome(SARS) topic received 875 citations and won the first place. The most cited documents in the field of coronavirus have 5 clusters; and the first cluster with 201 documents and with the topic of studying the structure of coronavirus is the largest one. Journal of Virology -- with the thematic range of genome structure and replication, virus identification, etc. -- ranked first with 35,383 citations. The most cited journals in the field of coronavirus are 5 thematic clusters, and the first one is the largest cluster with 121 journals and with the thematic domains of health policy, coronavirus, etc. Also, Woo won PCY first place with his specialization in identifying new microbes and emerging infectious diseases, and receiving 1491 citations. The most cited authors in the field of corona virus are in 6 thematic clusters; the first cluster with 195 authors in specialized field of virology and coronavirus is the largest cluster.
Conclusion: By identifying the highly cited scientific products in the field of coronavirus, efforts have been made to provide a comprehensive view of top documents, top journals, and top authors so that it can be a decision-making tool in the shortest possible time.
Marsa Gholamzadeh, Seyed Mohammad Ayyoubzadeh, Hoda Zahedi, Sharareh Rostam Niakan Kalhori,
Volume 15, Issue 3 (8-2021)
Volume 15, Issue 3 (8-2021)
Abstract
Background and Aim: Due to the important role of radiological images for identifying patients with COVID-19, creating a model based on deep learning methods was the main objective of this study.
Materials and Methods: 15,153 available chest images of normal, COVID-19, and pneumonia individuals which were in the Kaggle data repository was used as dataset of this research. Data preprocessing including normalizing images, integrating images and labeling into three categories, train, test and validation was performed. By Python language in the fastAI library based on convolution technique (CNN) and four architectures (ResNet, VGG MobileNet, AlexNet), nine models through transitional learning method were trained to recognize patients from healthy persons. Finally, the performance of these models was evaluated with indicators such as accuracy, sensitivity and specificity, and F-Measure.
Results: Of the nine generated models, the ResNet101 model has the highest ability to distinguish COVID-19 cases from other cases with 95.29% sensitivity. Other applied models showed more than 96% accuracy in correctly diagnosis of various cases in test phase. Finally, the ResNet101 model was able to demonstrate 98.4% accuracy in distinguishing between healthy and infected cases.
Conclusion: The obtained accuracy showed the accurate performance of developed model in detecting COVID-19 cases. Therefore, by implementing an application based on the developed model, physicians can be helped in accurate and early diagnosis of cases. an application based on the developed model, physicians can be helped in accurate and early diagnosis of infected cases.
Materials and Methods: 15,153 available chest images of normal, COVID-19, and pneumonia individuals which were in the Kaggle data repository was used as dataset of this research. Data preprocessing including normalizing images, integrating images and labeling into three categories, train, test and validation was performed. By Python language in the fastAI library based on convolution technique (CNN) and four architectures (ResNet, VGG MobileNet, AlexNet), nine models through transitional learning method were trained to recognize patients from healthy persons. Finally, the performance of these models was evaluated with indicators such as accuracy, sensitivity and specificity, and F-Measure.
Results: Of the nine generated models, the ResNet101 model has the highest ability to distinguish COVID-19 cases from other cases with 95.29% sensitivity. Other applied models showed more than 96% accuracy in correctly diagnosis of various cases in test phase. Finally, the ResNet101 model was able to demonstrate 98.4% accuracy in distinguishing between healthy and infected cases.
Conclusion: The obtained accuracy showed the accurate performance of developed model in detecting COVID-19 cases. Therefore, by implementing an application based on the developed model, physicians can be helped in accurate and early diagnosis of cases. an application based on the developed model, physicians can be helped in accurate and early diagnosis of infected cases.
Alireza Monadi Sefidan, Reza Afrisham,
Volume 16, Issue 3 (8-2022)
Volume 16, Issue 3 (8-2022)
Abstract
Background and Aim: Previous studies have shown that viral and host miRNAs play a role in the process of controlling or progressing the disease and can even be considered as therapeutic targets. Accordingly, the present review study was designed to evaluate the role of host miRNAs and Covid-19 virus in the disease process.
Materials and Methods: The current study was a review study that was conducted during 2012-2022. Studies were extracted from PubMed, Google Scholar, Web of Science and Scopus scientific databases. The researchers selected relevant resources and a summary of them was presented in this review.
Results: The present review study showed that some host miRNAs such as miR-23b-5p, miR-200c, and miR-125a-5p had an inhibitory effect on ACE2 receptor, while miR-3909, miR-4677, and miR-133a had a stimulatory effect on this receptor. Furthermore, host miR-98-5p had an inhibitory effect on TMPRSS2 gene expression. On the other hand, host miR-146a, miR-21, and miR-142 induced inflammation through MAPK and NF-Ƙβ signaling. While, host miR-124, miR-410, and miR-1336 inhibited factor STAT3 and prevented inflammation. Furthermore, host miR-302b and miR-372 targeted the mitochondrial antiviral signaling protein (MAVS), resulting in silencing of type 1 interferon signaling. It has also been established that host exosomal miR-7-5p, miR-24-3p, miR-145-5p, and miR-223-3p inhibited the replication of SARS-CoV-2 and the expression of S protein and their decreased expression in elderly and Diabetic subjects was associated with decreased inhibition of SARS-CoV-2 replication. Moreover, viral miR-359-5p regulated the expression of MYH9 (non-muscle myosin heavy chain 9), which caused virus invasion and release in the host cell.
Conclusion: This study showed that many miRNAs play a role in controlling or progressing the disease of Covid-19 and it is possible to treat the disease of Covid-19 by changing the expression of viral and host miRNA. However, more research is needed in this regard.
Materials and Methods: The current study was a review study that was conducted during 2012-2022. Studies were extracted from PubMed, Google Scholar, Web of Science and Scopus scientific databases. The researchers selected relevant resources and a summary of them was presented in this review.
Results: The present review study showed that some host miRNAs such as miR-23b-5p, miR-200c, and miR-125a-5p had an inhibitory effect on ACE2 receptor, while miR-3909, miR-4677, and miR-133a had a stimulatory effect on this receptor. Furthermore, host miR-98-5p had an inhibitory effect on TMPRSS2 gene expression. On the other hand, host miR-146a, miR-21, and miR-142 induced inflammation through MAPK and NF-Ƙβ signaling. While, host miR-124, miR-410, and miR-1336 inhibited factor STAT3 and prevented inflammation. Furthermore, host miR-302b and miR-372 targeted the mitochondrial antiviral signaling protein (MAVS), resulting in silencing of type 1 interferon signaling. It has also been established that host exosomal miR-7-5p, miR-24-3p, miR-145-5p, and miR-223-3p inhibited the replication of SARS-CoV-2 and the expression of S protein and their decreased expression in elderly and Diabetic subjects was associated with decreased inhibition of SARS-CoV-2 replication. Moreover, viral miR-359-5p regulated the expression of MYH9 (non-muscle myosin heavy chain 9), which caused virus invasion and release in the host cell.
Conclusion: This study showed that many miRNAs play a role in controlling or progressing the disease of Covid-19 and it is possible to treat the disease of Covid-19 by changing the expression of viral and host miRNA. However, more research is needed in this regard.
Zohreh Javanmard, Marziyhe Meraji, Mahsa Gholizad, Fatemeh Ameri,
Volume 17, Issue 4 (10-2023)
Volume 17, Issue 4 (10-2023)
Abstract
Background and Aim: With the increase of the covid-19 epidemic, wearable devices have received a lot of attention in the field of managing this disease. The present systematic review study was conducted with the aim of investigating the role of wearable devices in the management of the covid-19 disease.
Materials and Methods: The present study was conducted according to the guidelines of PRISMA. For this purpose, Web of Science, PubMed, and Scopus databases were searched to retrieve English articles without time limit, until August 16, 2022. The search strategy included the terms “Wearable Device” and “COVID-19”. The inclusion criteria for the study were original and English-language articles that have been carried out to design and implement wearable tools in managing Covid-19. All short articles, letters to the editor, conference abstracts, observational studies, review articles, as well as articles whose full version was not available and in a language other than English, as well as unimplemented items, were excluded from the study process. In order to evaluate the quality of articles, the AXIS evaluation tool was used to evaluate the quality of cross-sectional studies. After selecting the studies, data was collected based on the data extraction form. Then the data was analyzed through the content analysis method.
Results: Finally, 10 articles were included in the present review and the wearable devices introduced in them were examined. Seventy percent of wearable devices are used for symptom monitoring, health status, and quarantine, and 30% for diagnosis. The primary users of these tools were patients, the general public, doctors, and Authorities of statistics and information. The types of wearable devices used were bracelets and smart watches (60%), sensors (30%), pulse oximeters, and chest patches (10%).The most important capability and feature of wearable devices include transferring data and activities to mobile phones and low energy consumption. Using the AXIS quality assessment tool, four studies were rated as very good, five as good, and one as poor.
Conclusion: The review of studies showed that wearable devices provide many capabilities for disease monitoring and patient empowerment, disease diagnosis, and remote monitoring of vital signs of Covid-19 patients. These tools are presented in different forms. It is suggested to develop new tools with the aim of monitoring the covid-19 disease with an emphasis on the use of patients in the form of bracelets and smartwatches, and also the necessary attention should be paid to privacy and confidentiality issues.
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