Anita Venaik, R. Kumari, Utkarsh Venaik, A. Nayyar
{"title":"The Role of Machine Learning and Artificial Intelligence in Clinical Decisions and the Herbal Formulations Against COVID-19","authors":"Anita Venaik, R. Kumari, Utkarsh Venaik, A. Nayyar","doi":"10.4018/ijrqeh.298635","DOIUrl":null,"url":null,"abstract":"COVID-19 causes global health problems, and new technologies have to be established to detect, anticipate, diagnose, screen, and even trace COVID-19 by all health care experts. Several database searches are carried out in this literature-based study on machine learning (ML), artificial intelligence, computer-based molecular docking analysis (CBMDA), COVID-19, and herbal docking analysis. In the battle against different infectious diseases, ML, AI and CBMDA's past supporting data are involved. These devices have now been updated with advanced features and are part of the SARS-CoV-2 screening, prediction, diagnosis, contact tracing, and drug/vaccine production healthcare industries. This article aims to comprehensively analyse the essential role of ML and AI, and CBMDA in the screening, prediction, contact tracing, and production of herbal drugs for this virus and its associated epidemic.","PeriodicalId":36298,"journal":{"name":"International Journal of Reliable and Quality E-Healthcare","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Reliable and Quality E-Healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijrqeh.298635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Nursing","Score":null,"Total":0}
引用次数: 1
Abstract
COVID-19 causes global health problems, and new technologies have to be established to detect, anticipate, diagnose, screen, and even trace COVID-19 by all health care experts. Several database searches are carried out in this literature-based study on machine learning (ML), artificial intelligence, computer-based molecular docking analysis (CBMDA), COVID-19, and herbal docking analysis. In the battle against different infectious diseases, ML, AI and CBMDA's past supporting data are involved. These devices have now been updated with advanced features and are part of the SARS-CoV-2 screening, prediction, diagnosis, contact tracing, and drug/vaccine production healthcare industries. This article aims to comprehensively analyse the essential role of ML and AI, and CBMDA in the screening, prediction, contact tracing, and production of herbal drugs for this virus and its associated epidemic.
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