Early gastric cancer and Artificial Intelligence: Is it time for population screening?
Artificial intelligence
Diagnosis
Gastric cancer
Screening
Journal
Best practice & research. Clinical gastroenterology
ISSN: 1532-1916
Titre abrégé: Best Pract Res Clin Gastroenterol
Pays: Netherlands
ID NLM: 101120605
Informations de publication
Date de publication:
Historique:
received:
13
09
2020
revised:
18
10
2020
accepted:
05
11
2020
entrez:
26
6
2021
pubmed:
27
6
2021
medline:
21
7
2021
Statut:
ppublish
Résumé
Gastric cancer is a common cause of death worldwide and its early detection is crucial to improve its prognosis. Its incidence varies throughout countries, and screening has been found to be cost-effective at least in high-incidence regions. Identification of individuals harbouring preneoplastic lesions and their surveillance or of those with early gastric cancer are extremely important processes and endoscopy play a key role for this purpose. Unfortunately, also quality and accuracy for endoscopic detection varies among centres and endoscopists. Recent studies about Artificial Intelligence applied to endoscopic imaging show that these technologies perform very well and could be extremely useful for endoscopists to achieve the accuracy needed for gastric cancer screening. Nonetheless, as its introduction in this field is very recent, most studies are carried out offline and its results in clinical practice need to be further validated namely by incorporating all the components/dimensions of endoscopy from pre to post-assessment.
Identifiants
pubmed: 34172244
pii: S1521-6918(20)30045-7
doi: 10.1016/j.bpg.2020.101710
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
101710Informations de copyright
Copyright © 2020 Elsevier Ltd. All rights reserved.