{"title":"医疗保健机构大型语言模型：当前进展和未来机遇","authors":"Han Yuan","doi":"10.1002/med4.70000","DOIUrl":null,"url":null,"abstract":"<p>Agentic large language models (LLMs) combine vanilla LLMs’ reasoning, planning, and reflecting acquired from vast pre-trained datasets with specialized tools to enhance problem-solving capabilities. To understand the current progress and future opportunities of agentic LLMs for healthcare, this commentary conducted a comprehensive literature search in PubMed and summarized key takeaways.\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":100913,"journal":{"name":"Medicine Advances","volume":"3 1","pages":"37-41"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/med4.70000","citationCount":"0","resultStr":"{\"title\":\"Agentic Large Language Models for Healthcare: Current Progress and Future Opportunities\",\"authors\":\"Han Yuan\",\"doi\":\"10.1002/med4.70000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Agentic large language models (LLMs) combine vanilla LLMs’ reasoning, planning, and reflecting acquired from vast pre-trained datasets with specialized tools to enhance problem-solving capabilities. To understand the current progress and future opportunities of agentic LLMs for healthcare, this commentary conducted a comprehensive literature search in PubMed and summarized key takeaways.\\n <figure>\\n <div><picture>\\n <source></source></picture><p></p>\\n </div>\\n </figure></p>\",\"PeriodicalId\":100913,\"journal\":{\"name\":\"Medicine Advances\",\"volume\":\"3 1\",\"pages\":\"37-41\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/med4.70000\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medicine Advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/med4.70000\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medicine Advances","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/med4.70000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Agentic Large Language Models for Healthcare: Current Progress and Future Opportunities
Agentic large language models (LLMs) combine vanilla LLMs’ reasoning, planning, and reflecting acquired from vast pre-trained datasets with specialized tools to enhance problem-solving capabilities. To understand the current progress and future opportunities of agentic LLMs for healthcare, this commentary conducted a comprehensive literature search in PubMed and summarized key takeaways.
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