406. A SYSTEMATIC REVIEW AND META-ANALYSIS ON THE USE OF ARTIFICIAL INTELLIGENCE IN THE ENDOSCOPIC DIAGNOSIS OF ESOPHAGEAL CANCER
Rattachement africain : Afrique du Sud, gb. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Abstract Introduction Endoscopy plays a key role in the surveillance of patients with Barrett’s esophagus and the diagnosis of esophageal cancer. The subtleties of endoscopic interpretation are subject to clinical expertise, diagnostic skill, and thus human error. Therefore, artificial intelligence (AI) is increasingly being incorporated into endoscopy in order to improve diagnostic accuracy and early detection. This systematic review and meta-analysis consolidates the evidence on the use of AI in the endoscopic diagnosis of esophageal cancer. Methods The systematic review was carried out using Pubmed, MEDLINE and Ovid EMBASE databases as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies which described the role of AI in supporting endoscopic video or image diagnosis of esophageal cancer were included. A meta-analysis was also performed. Results 45 studies formed the qualitative and quantitative review. 14 studies with 1590 patients in total assessed the use of AI in endoscopic diagnosis of esophageal squamous cell carcinoma (ESCC)- the pooled sensitivity and specificity were 91.2% (84.3–95.2%) and 80% (64.3–89.9%). A further, 9 studies consisting of 478 patients overall explored the capabilities of AI in supporting the endoscopic diagnosis of esophageal adenocarcinoma (EAC), with a pooled sensitivity and specificity of 93.1% (86.8–96.4%) and 86.9% (81.7–90.7%). AI was often superior to endoscopists when diagnosing ESCC and improved the overall accuracy of both novice and expert endoscopists. Conclusion AI technology, as an adjunct to endoscopy has proven to be beneficial in early, accurate detection of esophageal malignancy. Multiple studies have shown superior diagnostic capabilities when comparing AI technology to endoscopists alone. Despite promising results, the application in real-time endoscopy is limited, and further multicenter trials are required to accurately assess its use in routine practice.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- 406. A SYSTEMATIC REVIEW AND META-ANALYSIS ON THE USE OF ARTIFICIAL INTELLIGENCE IN THE ENDOSCOPIC DIAGNOSIS OF ESOPHAGEAL CANCER
- Date Crossref
- 30/08/2023
- Éditeur
- Oxford University Press (OUP)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of the Witwatersrand University of the Witwatersrand, Afrique du Sud (code pays fourni par la source)Université ou école supérieure
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Oxford University Hospitals NHS Trust pays non établi dans la noticeÉtablissement de santé
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Imperial College London pays non établi dans la noticeUniversité ou école supérieure
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University of Oxford pays non établi dans la noticeUniversité ou école supérieure
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University of Witwatersrand Department of General Surgery Witwatersrand, Afrique du Sud (pays nommé en fin d’affiliation)Université ou école supérieure
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Oxford University Hospitals Department of General Surgery pays non établi dans la noticeUniversité ou école supérieure
University of the Witwatersrand (University of the Witwatersrand, Afrique du Sud), Oxford University Hospitals NHS Trust et Imperial College London, avec 3 autres affiliations. Pays d’affiliation : Afrique du Sud.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.