机器学习和人工智能在临床决策和抗COVID-19草药配方中的作用

Anita Venaik, R. Kumari, Utkarsh Venaik, A. Nayyar
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引用次数: 1

摘要

新冠肺炎导致全球健康问题,必须建立新技术,由所有卫生保健专家检测、预测、诊断、筛查甚至追踪新冠肺炎。在这项基于文献的研究中,对机器学习(ML)、人工智能、基于计算机的分子对接分析(CBMDA)、新冠肺炎和草药对接分析进行了一些数据库搜索。在对抗不同传染病的战斗中,ML、AI和CBMDA过去的支持数据都参与其中。这些设备现在已经更新了先进的功能,是严重急性呼吸系统综合征冠状病毒2型筛查、预测、诊断、接触者追踪和药物/疫苗生产医疗保健行业的一部分。本文旨在全面分析ML和AI以及CBMDA在该病毒及其相关流行病的筛查、预测、接触者追踪和草药生产中的重要作用。
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The Role of Machine Learning and Artificial Intelligence in Clinical Decisions and the Herbal Formulations Against COVID-19
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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