The expanding role of Artificial intelligence in medical diagnosis: from molecular diagnostics and multi-omics to digital health and medical imaging
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.
Authors
- Navid Pourzardosht (ORCID: https://orcid.org/0000-0001-7855-0967)
- Fahimeh Fattahi (ORCID: https://orcid.org/0000-0002-2563-0004)
- Faezeh Noorabad ghahroodi (ORCID: https://orcid.org/0000-0003-1331-2110)
- Pourya Nasirmoghadas
- Bahman Khalesi
- Saeed Khalili
- Zahra Sadat Hashemi
- Fatemeh Mahmoudian
- Aghdas Ramezani
- Marzieh Bagheri
Institutions
- Arak University of Medical Sciences (IR)
- Tarbiat Modares University (IR)
- Guilan University of Medical Sciences (IR)
- Motamed Cancer Institute (IR)
- Agricultural Research & Education Organization (IR)
- Semnan University of Medical Sciences (IR)
- Nano Carbon (Poland) (PL)
Publication Details
- Journal
- Expert Review of Molecular Diagnostics
- Published
- 2026-07-16
- DOI
- https://doi.org/10.1080/14737159.2026.2706000
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00