Welcome to the InfoSci Platform

Reference Hub

This research has been cited in:

Conference
Unveiling the Efficacy of Unani Medicine in Female Disorders Through Machine Learning: Current Challenges and Opportunities2023 20th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)10.1109/ICCWAMTIP60502.2023.10385245
Article
Hybrid Artificial Intelligence-Based Models for Prediction of Death Rate in India Due to COVID-19 TransmissionInternational Journal of Reliable and Quality E-Healthcare10.4018/IJRQEH.320480

The Role of Machine Learning and Artificial Intelligence in Clinical Decisions and the Herbal Formulations Against COVID-19

Anita Venaik, Rinki Kumari, Utkarsh Venaik, Anand Nayyar

Source Title: International Journal of Reliable and Quality E-Healthcare (IJRQEH)11(1)

ISSN: 2160-9551|EISSN: 2160-956X|EISBN13: 9781683182573|DOI: 10.4018/IJRQEH.2022010107

Cite Article Cite Article

MLA

Venaik, Anita, et al. "The Role of Machine Learning and Artificial Intelligence in Clinical Decisions and the Herbal Formulations Against COVID-19." IJRQEH vol.11, no.1 2022: pp.1-17. http://doi.org/10.4018/IJRQEH.2022010107

APA

Venaik, A., Kumari, R., Venaik, U., & Nayyar, A. (2022). The Role of Machine Learning and Artificial Intelligence in Clinical Decisions and the Herbal Formulations Against COVID-19. International Journal of Reliable and Quality E-Healthcare (IJRQEH), 11(1), 1-17. http://doi.org/10.4018/IJRQEH.2022010107

Chicago

Venaik, Anita, et al. "The Role of Machine Learning and Artificial Intelligence in Clinical Decisions and the Herbal Formulations Against COVID-19," International Journal of Reliable and Quality E-Healthcare (IJRQEH) 11, no.1: 1-17. http://doi.org/10.4018/IJRQEH.2022010107

Export Reference

Favorite Full-Issue Download

View Full Text HTML

View Full Text PDF

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.