{"title":"Strength, weakness, opportunities and challenges (SWOC) experience of histopathology image analysis, enhanced by artificial intelligence","authors":"Narendra Nath Singh, Ankita Tandon, Pavithra Jayasankar","doi":"10.1016/j.jobcr.2025.07.013","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial intelligence (AI) is reshaping the landscape of oral cancer diagnosis through the analysis of digital imaging. By promoting early detection, enhancing diagnostic precision, and enabling personalised treatment approaches, AI holds the potential to significantly improve patient outcomes. However, it is important to carefully consider concerns related to bias, costs, data quality, and regulatory standards. Histopathology image analysis is critical for precise and early diagnosis, particularly cancer detection. It improves consistency, decreases subjectivity, and enables accurate assessment. Its combination with AI allows for faster diagnostics, remote consultations, sophisticated research, and personalised treatment methods, making it an essential tool in modern pathology and healthcare. To fully realise its promise in improving patient care and diagnostics for oral cancer, strategic investments, multidisciplinary cooperation, and strong regulatory frameworks are essential. This narrative review highlights the potential and challenges that lie ahead while advocating for a balanced approach that combines technical innovation with ethical and regulatory vigilance based on a comprehensive literature search and our team's personal experience.</div></div>","PeriodicalId":16609,"journal":{"name":"Journal of oral biology and craniofacial research","volume":"15 5","pages":"Pages 1057-1063"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of oral biology and craniofacial research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212426825001575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) is reshaping the landscape of oral cancer diagnosis through the analysis of digital imaging. By promoting early detection, enhancing diagnostic precision, and enabling personalised treatment approaches, AI holds the potential to significantly improve patient outcomes. However, it is important to carefully consider concerns related to bias, costs, data quality, and regulatory standards. Histopathology image analysis is critical for precise and early diagnosis, particularly cancer detection. It improves consistency, decreases subjectivity, and enables accurate assessment. Its combination with AI allows for faster diagnostics, remote consultations, sophisticated research, and personalised treatment methods, making it an essential tool in modern pathology and healthcare. To fully realise its promise in improving patient care and diagnostics for oral cancer, strategic investments, multidisciplinary cooperation, and strong regulatory frameworks are essential. This narrative review highlights the potential and challenges that lie ahead while advocating for a balanced approach that combines technical innovation with ethical and regulatory vigilance based on a comprehensive literature search and our team's personal experience.
期刊介绍:
Journal of Oral Biology and Craniofacial Research (JOBCR)is the official journal of the Craniofacial Research Foundation (CRF). The journal aims to provide a common platform for both clinical and translational research and to promote interdisciplinary sciences in craniofacial region. JOBCR publishes content that includes diseases, injuries and defects in the head, neck, face, jaws and the hard and soft tissues of the mouth and jaws and face region; diagnosis and medical management of diseases specific to the orofacial tissues and of oral manifestations of systemic diseases; studies on identifying populations at risk of oral disease or in need of specific care, and comparing regional, environmental, social, and access similarities and differences in dental care between populations; diseases of the mouth and related structures like salivary glands, temporomandibular joints, facial muscles and perioral skin; biomedical engineering, tissue engineering and stem cells. The journal publishes reviews, commentaries, peer-reviewed original research articles, short communication, and case reports.