Current and future applications of artificial intelligence in pathology: a clinical perspective. Issue 7 (6th August 2020)

• Record Type: Journal Article
• Authors: Rakha, Emad A; Toss, Michael; Shiino, Sho; Gamble, Paul; Jaroensri, Ronnachai; Mermel, Craig H; Chen, Po-Hsuan Cameron
• Is Part Of: Journal of clinical pathology. Volume 74:Issue 7(2021)
• Page Start: 409
• Page End: 414
• Publication Date: 2020-08-06
• Subjects: telepathology -- breast -- pathology department, hospital; Pathology -- Periodicals; Pathology, Molecular -- Periodicals; 616.0705
• DOI: 10.1136/jclinpath-2020-206908
• Languages: English
• ISSNs: 0021-9746

Abstract

Abstract : During the last decade, a dramatic rise in the development and application of artificial intelligence (AI) tools for use in pathology services has occurred. This trend is often expected to continue and reshape the field of pathology in the coming years. The deployment of computational pathology and applications of AI tools can be considered as a paradigm shift that will change pathology services, making them more efficient and capable of meeting the needs of this era of precision medicine. Despite the success of AI models, the translational process from discovery to clinical applications has been slow. The gap between self-contained research and clinical environment may be too wide and has been largely neglected. In this review, we cover the current and prospective applications of AI in pathology. We examine its applications in diagnosis and prognosis, and we offer insights for considerations that could improve clinical applicability of these tools. Then, we discuss its potential to improve workflow efficiency, and its benefits in pathologist education. Finally, we review the factors that could influence adoption in clinical practices and the associated regulatory processes.