{"title":"The expanding role of artificial intelligence in medical diagnosis: from molecular diagnostics and multi-omics to digital health and medical imaging.","authors":"Aghdas Ramezani, Marzieh Bagheri, Fatemeh Mahmoudian, Fahimeh Fattahi, Faezeh Noorabad Ghahroodi, Pourya Nasirmoghadas, Navid Pourzardosht, Bahman Khalesi, Zahra Sadat Hashemi, Saeed Khalili","doi":"10.1080/14737159.2026.2706000","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The use of Artificial Intelligence (AI), especially Machine learning (ML) and Deep learning (DL), has led to a major shift in medical diagnosis. AI can assist medical professionals in medical diagnosis by its unique ability to analyze complex data from multiple sources, including medical images, gene sequences, and Electronic Health Records (EHRs).</p><p><strong>Areas covered: </strong>Its application in other clinical processes, such as risk classification, diagnostic workflows, and disease risk prediction from patient symptoms, can also speed up diagnosis, reduce costs, and improve diagnostic outcomes.</p><p><strong>Expert opinion: </strong>However, its effective use in the clinic necessitates addressing concerns about data privacy, rigorous validation, and the development of methods to reduce bias caused by medical data. By addressing these limitations, AI can be very effective in increasing medical professionals' knowledge and, consequently, improving patient outcomes.</p>","PeriodicalId":12113,"journal":{"name":"Expert Review of Molecular Diagnostics","volume":" ","pages":"755-774"},"PeriodicalIF":4.3000,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Review of Molecular Diagnostics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/14737159.2026.2706000","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PATHOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: The use of Artificial Intelligence (AI), especially Machine learning (ML) and Deep learning (DL), has led to a major shift in medical diagnosis. AI can assist medical professionals in medical diagnosis by its unique ability to analyze complex data from multiple sources, including medical images, gene sequences, and Electronic Health Records (EHRs).
Areas covered: Its application in other clinical processes, such as risk classification, diagnostic workflows, and disease risk prediction from patient symptoms, can also speed up diagnosis, reduce costs, and improve diagnostic outcomes.
Expert opinion: However, its effective use in the clinic necessitates addressing concerns about data privacy, rigorous validation, and the development of methods to reduce bias caused by medical data. By addressing these limitations, AI can be very effective in increasing medical professionals' knowledge and, consequently, improving patient outcomes.
期刊介绍:
Expert Review of Molecular Diagnostics (ISSN 1473-7159) publishes expert reviews of the latest advancements in the field of molecular diagnostics including the detection and monitoring of the molecular causes of disease that are being translated into groundbreaking diagnostic and prognostic technologies to be used in the clinical diagnostic setting.
Each issue of Expert Review of Molecular Diagnostics contains leading reviews on current and emerging topics relating to molecular diagnostics, subject to a rigorous peer review process; editorials discussing contentious issues in the field; diagnostic profiles featuring independent, expert evaluations of diagnostic tests; meeting reports of recent molecular diagnostics conferences and key paper evaluations featuring assessments of significant, recently published articles from specialists in molecular diagnostic therapy.
Expert Review of Molecular Diagnostics provides the forum for reporting the critical advances being made in this ever-expanding field, as well as the major challenges ahead in their clinical implementation. The journal delivers this information in concise, at-a-glance article formats: invaluable to a time-constrained community.