The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update.

Artificial intelligence Deep learning Digital histopathology

Journal

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
ISSN: 1542-7714
Titre abrégé: Clin Gastroenterol Hepatol
Pays: United States
ID NLM: 101160775

Informations de publication

Date de publication:
26 Dec 2023
Historique:
received: 28 08 2023
revised: 20 11 2023
accepted: 21 11 2023
medline: 29 12 2023
pubmed: 29 12 2023
entrez: 28 12 2023
Statut: aheadofprint

Résumé

Significant advances in artificial intelligence (AI) over the past decade may potentially lead to dramatic effects on clinical practice. Digitized histology represents an area ripe for AI implementation. We describe several current needs within the world of gastrointestinal histopathology, and outline, using currently studied models, how AI can potentially address them. We also highlight pitfalls as AI makes inroads into clinical practice.

Identifiants

pubmed: 38154727
pii: S1542-3565(23)01050-9
doi: 10.1016/j.cgh.2023.11.044
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 AGA Institute. Published by Elsevier Inc. All rights reserved.

Auteurs

D Chamil Codipilly (DC)

Division of Gastroenterology and Hepatology, Mayo Clinic Rochester, Minnesota, USA.

Shahriar Faghani (S)

Mayo AI Lab, Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.

Catherine Hagan (C)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.

Jason Lewis (J)

Department of Pathology, Mayo Clinic, Jacksonville, Florida, USA.

Bradley J Erickson (BJ)

Mayo AI Lab, Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.

Prasad G Iyer (PG)

Division of Gastroenterology and Hepatology, Mayo Clinic Rochester, Minnesota, USA. Electronic address: iyer.prasad@mayo.edu.

Classifications MeSH