Network Modeling and Analysis in Health Informatics and Bioinformatics最新文献

{"title":"Mathematical modeling of the outbreak of COVID-19.","authors":"Arvind Kumar Sinha,&nbsp;Nishant Namdev,&nbsp;Pradeep Shende","doi":"10.1007/s13721-021-00350-2","DOIUrl":"10.1007/s13721-021-00350-2","url":null,"abstract":"<p><p>The novel coronavirus SARS-Cov-2 is a pandemic condition and poses a massive menace to health. The governments of different countries and their various prohibitory steps to restrict the virus's expanse have changed individuals' communication processes. Due to physical and financial factors, the population's density is more likely to interact and spread the virus. We establish a mathematical model to present the spread of the COVID-19 in India and worldwide. By the simulation process, we find the infected cases, infected fatality rate, and recovery rate of the COVID-19. We validate the model by the rough set method. In the method, we obtain the accuracy for the infected case is 90.19%, an infection-fatality of COVID-19 is 94%, and the recovery is 85.57%, approximately the same as the actual situation reported WHO. This paper uses the generalized simulation process to predict the outbreak of COVID-19 for different continents. It gives the way of future trends of the COVID-19 outbreak till December 2021 and casts enlightenment about learning the drifts of the outbreak worldwide.</p>","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"11 1","pages":"5"},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8661390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10271862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using attack graphs to defend healthcare systems from cyberattacks: a longitudinal empirical study.","authors":"Hüseyin Ünözkan,&nbsp;Mehmet Ertem,&nbsp;Salaheddine Bendak","doi":"10.1007/s13721-022-00391-1","DOIUrl":"https://doi.org/10.1007/s13721-022-00391-1","url":null,"abstract":"<p><p>Cyber security encompasses a variety of financial, political, and social aspects with significant implications for the safety of individuals and organisations. Hospitals are among the least secure and most vulnerable organisations in terms of cybersecurity. Protecting medical records from cyberattacks is critical for protecting personal and financial records of those involved in medical institutions. Attack graphs, like in other systems, can be used to protect medical and hospital records from cyberattacks. In the current study, a total of 352 real-life cyberattacks on healthcare institutions using common vulnerability scoring system (CVSS) data were statistically examined to determine important trends and specifications in regard to those attacks. Following that, several machine learning techniques and an artificial neural network model were used to model industrial control systems (ICS) vulnerability data of those attacks. The average vulnerability score for attacks on healthcare IT systems was found to be very high. Moreover, this score was found to be higher in healthcare institutions which have experienced cyberattacks in the past and no mitigation actions were implemented. Using Python programming software, the most successful model that can be used in modelling cyberattacks on IT systems of healthcare institutions was found to be the <i>K</i>-nearest neighbours (KNN) algorithm. The model was then enhanced further and then it was tried to make predictions for future cyberattacks on IT systems of healthcare institutions. Results indicate that the overall score is critical indicating that medical records are, in general, at high risk and that there is a high risk of cyberattacks on medical records in healthcare institutions. It is recommended, therefore, that those institutions should take urgent precautionary measures to mitigate such a high risk of cyberattacks and to make them more secure, reliable, and robust.</p>","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":" ","pages":"52"},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668211/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40477420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors affecting the difference of protein supplements on physical fitness","authors":"D. Li","doi":"10.1007/s13721-021-00335-1","DOIUrl":"https://doi.org/10.1007/s13721-021-00335-1","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"35 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86017567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of pre-clustering on classification of heterogeneous protein data","authors":"Haneen Altartouri, H. Tamimi, Y. Ashhab","doi":"10.1007/s13721-021-00336-0","DOIUrl":"https://doi.org/10.1007/s13721-021-00336-0","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"26 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91280296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical mode decomposition based adaptive noise canceller for improved identification of exons in eukaryotes","authors":"M. Hota","doi":"10.1007/s13721-021-00346-y","DOIUrl":"https://doi.org/10.1007/s13721-021-00346-y","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"47 16","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72390671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico chemical profiling and identification of neuromodulators from Curcuma amada targeting acetylcholinesterase","authors":"M. Ali, Y. A. Munni, Raju Das, N. Akter, K. Das, Sarmistha Mitra, M. Hannan, R. Dash","doi":"10.1007/s13721-021-00334-2","DOIUrl":"https://doi.org/10.1007/s13721-021-00334-2","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"64 ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72429665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An effective feature extraction with deep neural network architecture for protein-secondary-structure prediction","authors":"Aditya Jayasimha, Rahul Mudambi, P. Pavan, B. M. Lokaksha, Sanjay S. Bankapur, Nagamma Patil","doi":"10.1007/s13721-021-00340-4","DOIUrl":"https://doi.org/10.1007/s13721-021-00340-4","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"51 2 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77469886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of key genes, pathways, and associated comorbidities in chikungunya infection: insights from system biology analysis","authors":"Lingjun Zhu, Xiaodong Wang, T. Asa, Md. Ali Hossain","doi":"10.1007/s13721-021-00331-5","DOIUrl":"https://doi.org/10.1007/s13721-021-00331-5","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"222 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79549561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study the inhibitory effect of some plant origin flavonoids against targetable cancer receptors GRP78 by molecular docking","authors":"F. Barzegar, Zahra Pahlavan Yali, M. Fatemi","doi":"10.1007/s13721-021-00308-4","DOIUrl":"https://doi.org/10.1007/s13721-021-00308-4","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"77 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80298192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network pharmacological evaluation for identifying novel drug-like molecules from ginger (Zingiber officinale Rosc.) against multiple disease targets, a computational biotechnology approach","authors":"Anish Nag, Ritesh Banerjee","doi":"10.1007/s13721-021-00330-6","DOIUrl":"https://doi.org/10.1007/s13721-021-00330-6","url":null,"abstract":"","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"21 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79774150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}