更安全的
背景(考古学)
风险分析(工程)
药物发现
抗性(生态学)
精密医学
新兴技术
计算机科学
数据科学
工程伦理学
医学
人工智能
工程类
生物信息学
生物
计算机安全
生态学
病理
古生物学
作者
Ferdinand Ndikuryayo,Xueyan Gong,Ge‐Fei Hao,Wen‐Chao Yang
摘要
ABSTRACT The increasing prevalence of drug resistance (DR) and pesticide resistance poses a significant threat to public health, necessitating the development of innovative strategies to discover more effective drugs and pesticides. In this context, artificial intelligence (AI) has emerged as a promising solution. This review examines the roles of AI in tackling DR. An analysis of current literature reveals that AI can enhance the drug discovery process, facilitating the faster creation of effective and safer medications. Furthermore, AI is crucial in predicting and elucidating the mechanisms of DR and pesticide resistance. By offering decision support to healthcare providers, AI‐driven precision medicine paves the way for personalized treatment options. Moreover, AI aids in identifying synergistic drug combinations essential for combating DR. Lessons from the recent use of AI in addressing DR demonstrate the potential of this versatile tool to offer solutions required for controlling infections and cancers in the era of DR. However, despite the advancements achieved, challenges such as data accessibility and ethical issues remain. This highlights the need for interdisciplinary collaboration and ethical consideration. Finally, we provide an outlook on future actions required to successfully implement AI‐powered technologies in drug and pesticide discovery.
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