{"title":"临床决策:从假设-演绎模型到知识增强的机器学习","authors":"Han Yuan","doi":"10.1002/med4.83","DOIUrl":null,"url":null,"abstract":"<p>Knowledge-enhanced machine learning can be conceptualized as a fusion of clinical knowledge and domain expertise extracted from traditional clinical decision making methods alongside powerful machine learning architectures. Knowledge-enhanced machine learning significantly improves current machine learning methods in terms of interpretability, generalizability, accuracy, and equity.\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":100913,"journal":{"name":"Medicine Advances","volume":"2 4","pages":"375-379"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/med4.83","citationCount":"0","resultStr":"{\"title\":\"Clinical decision making: Evolving from the hypothetico-deductive model to knowledge-enhanced machine learning\",\"authors\":\"Han Yuan\",\"doi\":\"10.1002/med4.83\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Knowledge-enhanced machine learning can be conceptualized as a fusion of clinical knowledge and domain expertise extracted from traditional clinical decision making methods alongside powerful machine learning architectures. Knowledge-enhanced machine learning significantly improves current machine learning methods in terms of interpretability, generalizability, accuracy, and equity.\\n <figure>\\n <div><picture>\\n <source></source></picture><p></p>\\n </div>\\n </figure></p>\",\"PeriodicalId\":100913,\"journal\":{\"name\":\"Medicine Advances\",\"volume\":\"2 4\",\"pages\":\"375-379\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/med4.83\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medicine Advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/med4.83\",\"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/med4.83","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clinical decision making: Evolving from the hypothetico-deductive model to knowledge-enhanced machine learning
Knowledge-enhanced machine learning can be conceptualized as a fusion of clinical knowledge and domain expertise extracted from traditional clinical decision making methods alongside powerful machine learning architectures. Knowledge-enhanced machine learning significantly improves current machine learning methods in terms of interpretability, generalizability, accuracy, and equity.