| Literature DB >> 32763920 |
Emad A Rakha1, Michael Toss2, Sho Shiino2, Paul Gamble3, Ronnachai Jaroensri3, Craig H Mermel3, Po-Hsuan Cameron Chen3.
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. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.Keywords: breast; pathology department, hospital; telepathology
Mesh:
Year: 2020 PMID: 32763920 DOI: 10.1136/jclinpath-2020-206908
Source DB: PubMed Journal: J Clin Pathol ISSN: 0021-9746 Impact factor: 3.411