Yan Guo, Heyuan Wang, Xue Ren, Tengjiao Wang, Wei Chen, Ziming Xu, Hui Ge
{"title":"GPTs能加速中医智能诊疗的发展吗?调查与实证分析","authors":"Yan Guo, Heyuan Wang, Xue Ren, Tengjiao Wang, Wei Chen, Ziming Xu, Hui Ge","doi":"10.1111/jebm.70004","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <p>Intelligent traditional Chinese medicine (TCM) is a key pathway toward the modernization and globalization of TCM in the era of artificial intelligence. Due to its unique terminology and diagnostic framework, TCM's intelligentization process has long faced a range of challenges, from the digitization and formalization of knowledge bases to the differentiation of syndromes and personalized treatment. Recently, the advent of large language models (LLMs) like GPTs has marked a transformative milestone in semantic understanding tasks, attracting widespread attention from the medical, academic, and industrial communities. Nonetheless, LLMs often suffer from accuracy and logical reasoning limitations within specific fields and may manifest hallucinations in the generative outputs. Through a comprehensive review of existing literature and empirical analyses, this study delves into the potential and challenges of adapting LLMs to TCM. Promising perspectives on future developments at this innovative intersection are discussed.</p>\n </section>\n </div>","PeriodicalId":16090,"journal":{"name":"Journal of Evidence‐Based Medicine","volume":"18 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can GPTs Accelerate the Development of Intelligent Diagnosis and Treatment in Traditional Chinese Medicine? A Survey and Empirical Analysis\",\"authors\":\"Yan Guo, Heyuan Wang, Xue Ren, Tengjiao Wang, Wei Chen, Ziming Xu, Hui Ge\",\"doi\":\"10.1111/jebm.70004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <p>Intelligent traditional Chinese medicine (TCM) is a key pathway toward the modernization and globalization of TCM in the era of artificial intelligence. Due to its unique terminology and diagnostic framework, TCM's intelligentization process has long faced a range of challenges, from the digitization and formalization of knowledge bases to the differentiation of syndromes and personalized treatment. Recently, the advent of large language models (LLMs) like GPTs has marked a transformative milestone in semantic understanding tasks, attracting widespread attention from the medical, academic, and industrial communities. Nonetheless, LLMs often suffer from accuracy and logical reasoning limitations within specific fields and may manifest hallucinations in the generative outputs. Through a comprehensive review of existing literature and empirical analyses, this study delves into the potential and challenges of adapting LLMs to TCM. Promising perspectives on future developments at this innovative intersection are discussed.</p>\\n </section>\\n </div>\",\"PeriodicalId\":16090,\"journal\":{\"name\":\"Journal of Evidence‐Based Medicine\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Evidence‐Based Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jebm.70004\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Evidence‐Based Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jebm.70004","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Can GPTs Accelerate the Development of Intelligent Diagnosis and Treatment in Traditional Chinese Medicine? A Survey and Empirical Analysis
Intelligent traditional Chinese medicine (TCM) is a key pathway toward the modernization and globalization of TCM in the era of artificial intelligence. Due to its unique terminology and diagnostic framework, TCM's intelligentization process has long faced a range of challenges, from the digitization and formalization of knowledge bases to the differentiation of syndromes and personalized treatment. Recently, the advent of large language models (LLMs) like GPTs has marked a transformative milestone in semantic understanding tasks, attracting widespread attention from the medical, academic, and industrial communities. Nonetheless, LLMs often suffer from accuracy and logical reasoning limitations within specific fields and may manifest hallucinations in the generative outputs. Through a comprehensive review of existing literature and empirical analyses, this study delves into the potential and challenges of adapting LLMs to TCM. Promising perspectives on future developments at this innovative intersection are discussed.
期刊介绍:
The Journal of Evidence-Based Medicine (EMB) is an esteemed international healthcare and medical decision-making journal, dedicated to publishing groundbreaking research outcomes in evidence-based decision-making, research, practice, and education. Serving as the official English-language journal of the Cochrane China Centre and West China Hospital of Sichuan University, we eagerly welcome editorials, commentaries, and systematic reviews encompassing various topics such as clinical trials, policy, drug and patient safety, education, and knowledge translation.