Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force.
Journal
Gastrointestinal endoscopy
ISSN: 1097-6779
Titre abrégé: Gastrointest Endosc
Pays: United States
ID NLM: 0010505
Informations de publication
Date de publication:
05 2023
05 2023
Historique:
received:
29
09
2022
accepted:
09
10
2022
medline:
21
4
2023
pubmed:
11
2
2023
entrez:
10
2
2023
Statut:
ppublish
Résumé
In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and reliability need to be rigorously assessed. In this article, we provide a guiding framework for all stakeholders in the endoscopy AI ecosystem regarding the standards, metrics, and evaluation methods for emerging and existing AI applications to aid in their clinical adoption and implementation. We also provide guidance and best practices for evaluation of AI technologies as they mature in the endoscopy space. Note, this is a living document; periodic updates will be published as progress is made and applications evolve in the field of AI in endoscopy.
Identifiants
pubmed: 36764886
pii: S0016-5107(22)02052-1
doi: 10.1016/j.gie.2022.10.016
pii:
doi:
Types de publication
Practice Guideline
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
815-824.e1Commentaires et corrections
Type : ErratumIn
Informations de copyright
Copyright © 2023 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.