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人工智能在传染病和抗菌药物耐药性方面的挑战与应用

Challenges and applications of artificial intelligence in infectious diseases and antimicrobial resistance.

作者信息

Cesaro Angela, Hoffman Samuel C, Das Payel, de la Fuente-Nunez Cesar

机构信息

Machine Biology Group, Department of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Department of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

NPJ Antimicrob Resist. 2025 Jan 7;3(1):2. doi: 10.1038/s44259-024-00068-x.

Abstract

Artificial intelligence (AI) has transformed infectious disease control, enhancing rapid diagnosis and antibiotic discovery. While conventional tests delay diagnosis, AI-driven methods like machine learning and deep learning assist in pathogen detection, resistance prediction, and drug discovery. These tools improve antibiotic stewardship and identify effective compounds such as antimicrobial peptides and small molecules. This review explores AI applications in diagnostics, therapy, and drug discovery, emphasizing both strengths and areas needing improvement.

摘要

人工智能(AI)已经改变了传染病控制方式,提高了快速诊断能力并促进了抗生素的发现。传统检测方法会延迟诊断,而机器学习和深度学习等人工智能驱动的方法有助于病原体检测、耐药性预测和药物发现。这些工具改善了抗生素管理,并识别出有效的化合物,如抗菌肽和小分子。本综述探讨了人工智能在诊断、治疗和药物发现方面的应用,强调了其优势和需要改进的领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c76c/11721440/a3d19b6477a7/44259_2024_68_Fig1_HTML.jpg

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