Autumn Arnold, Stewart McLellan, Jonathan M Stokes
{"title":"人工智能如何帮助我们战胜抗生素耐药性。","authors":"Autumn Arnold, Stewart McLellan, Jonathan M Stokes","doi":"10.1038/s44259-025-00085-4","DOIUrl":null,"url":null,"abstract":"<p><p>Antimicrobial resistance (AMR) is an urgent public health threat. Advancements in artificial intelligence (AI) and increases in computational power have resulted in the adoption of AI for biological tasks. This review explores the application of AI in bacterial infection diagnostics, AMR surveillance, and antibiotic discovery. We summarize contemporary AI models applied to each of these domains, important considerations when applying AI across diverse tasks, and current limitations in the field.</p>","PeriodicalId":520007,"journal":{"name":"npj antimicrobials and resistance","volume":"3 1","pages":"18"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906734/pdf/","citationCount":"0","resultStr":"{\"title\":\"How AI can help us beat AMR.\",\"authors\":\"Autumn Arnold, Stewart McLellan, Jonathan M Stokes\",\"doi\":\"10.1038/s44259-025-00085-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Antimicrobial resistance (AMR) is an urgent public health threat. Advancements in artificial intelligence (AI) and increases in computational power have resulted in the adoption of AI for biological tasks. This review explores the application of AI in bacterial infection diagnostics, AMR surveillance, and antibiotic discovery. We summarize contemporary AI models applied to each of these domains, important considerations when applying AI across diverse tasks, and current limitations in the field.</p>\",\"PeriodicalId\":520007,\"journal\":{\"name\":\"npj antimicrobials and resistance\",\"volume\":\"3 1\",\"pages\":\"18\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906734/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj antimicrobials and resistance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s44259-025-00085-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj antimicrobials and resistance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s44259-025-00085-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Antimicrobial resistance (AMR) is an urgent public health threat. Advancements in artificial intelligence (AI) and increases in computational power have resulted in the adoption of AI for biological tasks. This review explores the application of AI in bacterial infection diagnostics, AMR surveillance, and antibiotic discovery. We summarize contemporary AI models applied to each of these domains, important considerations when applying AI across diverse tasks, and current limitations in the field.