Open AccessThe Role of Machine Learning and Artificial Intelligence in Clinical Decisions and the Herbal Formulations Against COVID-19
Author(s) -
Anita Venaik,
Reena Kumari,
Utkarsh Venaik,
Anand Nayyar
Publication year - 2022
Publication title -
international journal of reliable and quality e-healthcare
Language(s) - English
Resource type - Journals
eISSN - 2160-956X
pISSN - 2160-9551
DOI - 10.4018/ijrqeh.2022010107
Subject(s) - covid-19 , battle , contact tracing , artificial intelligence , computer science , tracing , health care , machine learning , coronavirus , data science , medicine , infectious disease (medical specialty) , virology , disease , archaeology , pathology , economics , history , economic growth , operating system , outbreak
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.