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Cited by in F6Publishing
For: Ashat M, Klair JS, Singh D, Murali AR, Krishnamoorthi R. Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis.Endosc Int Open. 2021;9:E513-E521. [PMID: 33816771 DOI: 10.1055/a-1341-0457] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
Number Citing Articles
1 Yoo BS, D'Souza SM, Houston K, Patel A, Lau J, Elmahdi A, Parekh PJ, Johnson D. Artificial intelligence and colonoscopy − enhancements and improvements. Artif Intell Gastrointest Endosc 2021; 2(4): 157-167 [DOI: 10.37126/aige.v2.i4.157] [Reference Citation Analysis]
2 Ainechi D, Misawa M, Barua I, Larsen SLV, Paulsen V, Garborg KK, Aabakken L, Tønnesen CJ, Løberg M, Kalager M, Kudo SE, Hotta K, Ohtsuka K, Saito S, Ikematsu H, Saito Y, Matsuda T, Itoh H, Mori K, Bretthauer M, Mori Y. Impact of artificial intelligence on colorectal polyp detection for early-career endoscopists: an international comparative study. Scand J Gastroenterol 2022;:1-6. [PMID: 35605150 DOI: 10.1080/00365521.2022.2070436] [Reference Citation Analysis]
3 Nogueira-rodríguez A, Domínguez-carbajales R, Campos-tato F, Herrero J, Puga M, Remedios D, Rivas L, Sánchez E, Iglesias Á, Cubiella J, Fdez-riverola F, López-fernández H, Reboiro-jato M, Glez-peña D. Real-time polyp detection model using convolutional neural networks. Neural Comput & Applic. [DOI: 10.1007/s00521-021-06496-4] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
4 Pan H, Cai M, Liao Q, Jiang Y, Liu Y, Zhuang X, Yu Y. Artificial Intelligence-Aid Colonoscopy Vs. Conventional Colonoscopy for Polyp and Adenoma Detection: A Systematic Review of 7 Discordant Meta-Analyses. Front Med (Lausanne) 2021;8:775604. [PMID: 35096870 DOI: 10.3389/fmed.2021.775604] [Reference Citation Analysis]
5 Matsui H, Kamba S, Horiuchi H, Takahashi S, Nishikawa M, Fukuda A, Tonouchi A, Kutsuna N, Shimahara Y, Tamai N, Sumiyama K. Detection Accuracy and Latency of Colorectal Lesions with Computer-Aided Detection System Based on Low-Bias Evaluation. Diagnostics (Basel) 2021;11:1922. [PMID: 34679619 DOI: 10.3390/diagnostics11101922] [Reference Citation Analysis]