{"title":"人工智能集成微流控技术在分析和生物分析应用中的最新进展综述","authors":"","doi":"10.1016/j.trac.2024.118004","DOIUrl":null,"url":null,"abstract":"<div><div>In today's biomedical research, the pursuit of diagnostic tools boasting maximum precision and accuracy while minimizing sample volume and pre-treatment requirements, has intensified. In this regard, microfluidic devices offer promising solutions by reducing sample size and overall research costs. However, the intricate and time-consuming nature of the data obtained from such devices poses significant challenges. To overcome these difficulties, researchers have increasingly turned to the integration of artificial intelligence (AI) with microfluidic platforms, resulting in the emergence of “<em>AI-integrated microfluidics</em>”. Recent advances in computer-related fields can transform AI from a theoretical science to a useful tool for various studies which is anticipated to become an integral part of human life. This review provides a comprehensive overview of various approaches for combining AI algorithms with microfluidic platforms for analytical and bioanalytical assessments. Highlighting applications ranging from cell classification and disease detection to point-of-care diagnostics, the paper underscores the transformative potential of AI-integrated microfluidics in advancing biomedical research and clinical diagnostics.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":11.8000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A review on recent advances of AI-integrated microfluidics for analytical and bioanalytical applications\",\"authors\":\"\",\"doi\":\"10.1016/j.trac.2024.118004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In today's biomedical research, the pursuit of diagnostic tools boasting maximum precision and accuracy while minimizing sample volume and pre-treatment requirements, has intensified. In this regard, microfluidic devices offer promising solutions by reducing sample size and overall research costs. However, the intricate and time-consuming nature of the data obtained from such devices poses significant challenges. To overcome these difficulties, researchers have increasingly turned to the integration of artificial intelligence (AI) with microfluidic platforms, resulting in the emergence of “<em>AI-integrated microfluidics</em>”. Recent advances in computer-related fields can transform AI from a theoretical science to a useful tool for various studies which is anticipated to become an integral part of human life. This review provides a comprehensive overview of various approaches for combining AI algorithms with microfluidic platforms for analytical and bioanalytical assessments. Highlighting applications ranging from cell classification and disease detection to point-of-care diagnostics, the paper underscores the transformative potential of AI-integrated microfluidics in advancing biomedical research and clinical diagnostics.</div></div>\",\"PeriodicalId\":439,\"journal\":{\"name\":\"Trends in Analytical Chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.8000,\"publicationDate\":\"2024-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in Analytical Chemistry\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0165993624004874\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Analytical Chemistry","FirstCategoryId":"1","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165993624004874","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
A review on recent advances of AI-integrated microfluidics for analytical and bioanalytical applications
In today's biomedical research, the pursuit of diagnostic tools boasting maximum precision and accuracy while minimizing sample volume and pre-treatment requirements, has intensified. In this regard, microfluidic devices offer promising solutions by reducing sample size and overall research costs. However, the intricate and time-consuming nature of the data obtained from such devices poses significant challenges. To overcome these difficulties, researchers have increasingly turned to the integration of artificial intelligence (AI) with microfluidic platforms, resulting in the emergence of “AI-integrated microfluidics”. Recent advances in computer-related fields can transform AI from a theoretical science to a useful tool for various studies which is anticipated to become an integral part of human life. This review provides a comprehensive overview of various approaches for combining AI algorithms with microfluidic platforms for analytical and bioanalytical assessments. Highlighting applications ranging from cell classification and disease detection to point-of-care diagnostics, the paper underscores the transformative potential of AI-integrated microfluidics in advancing biomedical research and clinical diagnostics.
期刊介绍:
TrAC publishes succinct and critical overviews of recent advancements in analytical chemistry, designed to assist analytical chemists and other users of analytical techniques. These reviews offer excellent, up-to-date, and timely coverage of various topics within analytical chemistry. Encompassing areas such as analytical instrumentation, biomedical analysis, biomolecular analysis, biosensors, chemical analysis, chemometrics, clinical chemistry, drug discovery, environmental analysis and monitoring, food analysis, forensic science, laboratory automation, materials science, metabolomics, pesticide-residue analysis, pharmaceutical analysis, proteomics, surface science, and water analysis and monitoring, these critical reviews provide comprehensive insights for practitioners in the field.