{"title":"将人工智能融入临床检验医学:进步与挑战","authors":"Heying Xie, Yin Jia, Shanrong Liu","doi":"10.1002/INMD.20230056","DOIUrl":null,"url":null,"abstract":"<p>Artificial intelligence (AI)-driven analysis of comprehensive clinical parameters is bringing about a significant transformation in traditional routine clinical laboratory testing. This transformation impacts the prediction, prevention, diagnosis, and prognosis of human diseases. AI possesses the capability to efficiently analyze and process vast and intricate datasets, thereby facilitating the development of diverse and efficient diagnostic or predictive models. This advancement is fueling significant improvements in laboratory quality, automation, and the accuracy of diagnoses. In this context, we conducted a thorough review and discussion on the progression of AI applications in clinical laboratory medicine, encompassing advancements, implementation, and challenges. Our conclusion underscores that integrating AI into clinical laboratory testing will notably propel personalized precision medicine forward and enhance diagnostic accuracy, especially benefiting patients for whom accurate diagnoses are elusive through traditional laboratory testing systems.</p>","PeriodicalId":100686,"journal":{"name":"Interdisciplinary Medicine","volume":"2 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/INMD.20230056","citationCount":"0","resultStr":"{\"title\":\"Integration of artificial intelligence in clinical laboratory medicine: Advancements and challenges\",\"authors\":\"Heying Xie, Yin Jia, Shanrong Liu\",\"doi\":\"10.1002/INMD.20230056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Artificial intelligence (AI)-driven analysis of comprehensive clinical parameters is bringing about a significant transformation in traditional routine clinical laboratory testing. This transformation impacts the prediction, prevention, diagnosis, and prognosis of human diseases. AI possesses the capability to efficiently analyze and process vast and intricate datasets, thereby facilitating the development of diverse and efficient diagnostic or predictive models. This advancement is fueling significant improvements in laboratory quality, automation, and the accuracy of diagnoses. In this context, we conducted a thorough review and discussion on the progression of AI applications in clinical laboratory medicine, encompassing advancements, implementation, and challenges. Our conclusion underscores that integrating AI into clinical laboratory testing will notably propel personalized precision medicine forward and enhance diagnostic accuracy, especially benefiting patients for whom accurate diagnoses are elusive through traditional laboratory testing systems.</p>\",\"PeriodicalId\":100686,\"journal\":{\"name\":\"Interdisciplinary Medicine\",\"volume\":\"2 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/INMD.20230056\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Interdisciplinary Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/INMD.20230056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interdisciplinary Medicine","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/INMD.20230056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integration of artificial intelligence in clinical laboratory medicine: Advancements and challenges
Artificial intelligence (AI)-driven analysis of comprehensive clinical parameters is bringing about a significant transformation in traditional routine clinical laboratory testing. This transformation impacts the prediction, prevention, diagnosis, and prognosis of human diseases. AI possesses the capability to efficiently analyze and process vast and intricate datasets, thereby facilitating the development of diverse and efficient diagnostic or predictive models. This advancement is fueling significant improvements in laboratory quality, automation, and the accuracy of diagnoses. In this context, we conducted a thorough review and discussion on the progression of AI applications in clinical laboratory medicine, encompassing advancements, implementation, and challenges. Our conclusion underscores that integrating AI into clinical laboratory testing will notably propel personalized precision medicine forward and enhance diagnostic accuracy, especially benefiting patients for whom accurate diagnoses are elusive through traditional laboratory testing systems.