• Junjie Mi, Xiaofang Han, Rong Wang, Ruijun Ma, and Danyu Zhao.
• Digestive Endoscopy Center, Shanxi Provincial People's Hospital, Taiyuan, China.
• Int. J. Clin. Pract. 2022 Jan 1; 2022: 9338139.

AimAs the completed studies have small sample sizes and different algorithms, a meta-analysis was conducted to assess the accuracy of WCE in identifying polyps using deep learning.MethodTwo independent reviewers searched PubMed, Embase, the Web of Science, and the Cochrane Library for potentially eligible studies published up to December 8, 2021, which were analysed on a per-image basis. STATA RevMan and Meta-DiSc were used to conduct this meta-analysis. A random effects model was used, and a subgroup and regression analysis was performed to explore sources of heterogeneity.ResultsEight studies published between 2017 and 2021 included 819 patients, and 18,414 frames were eventually included in the meta-analysis. The summary estimates for the WCE in identifying polyps by deep learning were sensitivity 0.97 (95% confidence interval (CI), 0.95-0.98); specificity 0.97 (95% CI, 0.94-0.98); positive likelihood ratio 27.19 (95% CI, 15.32-50.42); negative likelihood ratio 0.03 (95% CI 0.02-0.05); diagnostic odds ratio 873.69 (95% CI, 387.34-1970.74); and the area under the sROC curve 0.99.ConclusionWCE uses deep learning to identify polyps with high accuracy, but multicentre prospective randomized controlled studies are needed in the future.Copyright © 2022 Junjie Mi et al.

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