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For: Wang P, Liu P, Glissen Brown JR, Berzin TM, Zhou G, Lei S, Liu X, Li L, Xiao X. Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study. Gastroenterology. 2020;159:1252-1261.e5. [PMID: 32562721 DOI: 10.1053/j.gastro.2020.06.023] [Cited by in Crossref: 28] [Cited by in F6Publishing: 25] [Article Influence: 14.0] [Reference Citation Analysis]
Number Citing Articles
1 Glissen Brown JR, Mansour NM, Wang P, Chuchuca MA, Minchenberg SB, Chandnani M, Liu L, Gross SA, Sengupta N, Berzin TM. Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial). Clin Gastroenterol Hepatol 2021:S1542-3565(21)00973-3. [PMID: 34530161 DOI: 10.1016/j.cgh.2021.09.009] [Reference Citation Analysis]
2 Okagawa Y, Abe S, Yamada M, Oda I, Saito Y. Artificial Intelligence in Endoscopy. Dig Dis Sci 2021. [PMID: 34155567 DOI: 10.1007/s10620-021-07086-z] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Corley DA, Peek RM Jr, Simpson BA. Paradigm-Shifting Research in Gastroenterology, Hepatology, and Nutrition: A Top 20 List of Articles Published in 2020. Gastroenterology 2021;160:979-81. [PMID: 33548197 DOI: 10.1053/j.gastro.2021.01.023] [Reference Citation Analysis]
4 Liu P, Wang P, Glissen Brown JR, Berzin TM, Zhou G, Liu W, Xiao X, Chen Z, Zhang Z, Zhou C, Lei L, Xiong F, Li L, Liu X. The single-monitor trial: an embedded CADe system increased adenoma detection during colonoscopy: a prospective randomized study.Therap Adv Gastroenterol. 2020;13:1756284820979165. [PMID: 33403003 DOI: 10.1177/1756284820979165] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
5 Misawa M, Kudo SE, Mori Y, Maeda Y, Ogawa Y, Ichimasa K, Kudo T, Wakamura K, Hayashi T, Miyachi H, Baba T, Ishida F, Itoh H, Oda M, Mori K. Current status and future perspective on artificial intelligence for lower endoscopy. Dig Endosc 2021;33:273-84. [PMID: 32969051 DOI: 10.1111/den.13847] [Cited by in Crossref: 3] [Article Influence: 1.5] [Reference Citation Analysis]
6 Yamada M, Saito Y, Yamada S, Kondo H, Hamamoto R. Detection of flat colorectal neoplasia by artificial intelligence: A systematic review. Best Pract Res Clin Gastroenterol 2021;52-53:101745. [PMID: 34172250 DOI: 10.1016/j.bpg.2021.101745] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
7 Wang P, Berzin TM, Glissen Brown JR. Reply. Gastroenterology 2021;160:2212-3. [PMID: 33516702 DOI: 10.1053/j.gastro.2021.01.217] [Reference Citation Analysis]
8 Lui TKL, Leung WK. Is artificial intelligence the final answer to missed polyps in colonoscopy? World J Gastroenterol 2020; 26(35): 5248-5255 [PMID: 32994685 DOI: 10.3748/wjg.v26.i35.5248] [Cited by in CrossRef: 1] [Article Influence: 0.5] [Reference Citation Analysis]
9 Lazăr DC, Avram MF, Faur AC, Romoşan I, Goldiş A. The role of computer-assisted systems for upper-endoscopy quality monitoring and assessment of gastric lesions. Gastroenterol Rep (Oxf) 2021;9:185-204. [PMID: 34316369 DOI: 10.1093/gastro/goab008] [Reference Citation Analysis]
10 Wang JZ, Zhang Y, Guo Q. Thoughts on factors related to colonoscopy quality. Shijie Huaren Xiaohua Zazhi 2021; 29(17): 977-983 [DOI: 10.11569/wcjd.v29.i17.977] [Reference Citation Analysis]
11 Nazarian S, Glover B, Ashrafian H, Darzi A, Teare J. Diagnostic Accuracy of Artificial Intelligence and Computer-Aided Diagnosis for the Detection and Characterization of Colorectal Polyps: Systematic Review and Meta-analysis. J Med Internet Res 2021;23:e27370. [PMID: 34259645 DOI: 10.2196/27370] [Reference Citation Analysis]
12 Pacal I, Karaboga D. A robust real-time deep learning based automatic polyp detection system. Comput Biol Med 2021;134:104519. [PMID: 34090014 DOI: 10.1016/j.compbiomed.2021.104519] [Reference Citation Analysis]
13 Oka A, Ishimura N, Ishihara S. A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology. Diagnostics (Basel) 2021;11:1719. [PMID: 34574060 DOI: 10.3390/diagnostics11091719] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
14 Zhuang H, Bao A, Tan Y, Wang H, Xie Q, Qiu M, Xiong W, Liao F. Application and prospect of artificial intelligence in digestive endoscopy. Expert Rev Gastroenterol Hepatol 2021;:1-11. [PMID: 34937459 DOI: 10.1080/17474124.2022.2020646] [Reference Citation Analysis]
15 Zhao SB, Yang W, Wang SL, Pan P, Wang RD, Chang X, Sun ZQ, Fu XH, Shang H, Wu JR, Chen LZ, Chang J, Song P, Miao YL, He SX, Miao L, Jiang HQ, Wang W, Yang X, Dong YH, Lin H, Chen Y, Gao J, Meng QQ, Jin ZD, Li ZS, Bai Y. Establishment and validation of a computer-assisted colonic polyp localization system based on deep learning. World J Gastroenterol 2021; 27(31): 5232-5246 [PMID: 34497447 DOI: 10.3748/wjg.v27.i31.5232] [Reference Citation Analysis]
16 Tontini GE, Neumann H. Artificial intelligence: Thinking outside the box. Best Pract Res Clin Gastroenterol 2021;52-53:101720. [PMID: 34172247 DOI: 10.1016/j.bpg.2020.101720] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
17 Taghiakbari M, Mori Y, von Renteln D. Artificial intelligence-assisted colonoscopy: A review of current state of practice and research. World J Gastroenterol 2021; 27(47): 8103-8122 [DOI: 10.3748/wjg.v27.i47.8103] [Reference Citation Analysis]
18 Correia FP, Lourenço LC. Artificial intelligence application in diagnostic gastrointestinal endoscopy - Deus ex machina? World J Gastroenterol 2021; 27(32): 5351-5361 [PMID: 34539137 DOI: 10.3748/wjg.v27.i32.5351] [Reference Citation Analysis]
19 Pannala R, Krishnan K, Melson J, Parsi MA, Schulman AR, Sullivan S, Trikudanathan G, Trindade AJ, Watson RR, Maple JT, Lichtenstein DR. Artificial intelligence in gastrointestinal endoscopy. VideoGIE. 2020;5:598-613. [PMID: 33319126 DOI: 10.1016/j.vgie.2020.08.013] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 2.0] [Reference Citation Analysis]
20 Ahmad OF, Mori Y, Misawa M, Kudo SE, Anderson JT, Bernal J, Berzin TM, Bisschops R, Byrne MF, Chen PJ, East JE, Eelbode T, Elson DS, Gurudu SR, Histace A, Karnes WE, Repici A, Singh R, Valdastri P, Wallace MB, Wang P, Stoyanov D, Lovat LB. Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method.Endoscopy. 2021;53:893-901. [PMID: 33167043 DOI: 10.1055/a-1306-7590] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
21 Antonelli G, Gkolfakis P, Tziatzios G, Papanikolaou IS, Triantafyllou K, Hassan C. Artificial intelligence-aided colonoscopy: Recent developments and future perspectives. World J Gastroenterol 2020; 26(47): 7436-7443 [PMID: 33384546 DOI: 10.3748/wjg.v26.i47.7436] [Cited by in CrossRef: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
22 Li JW, Ang TL. Colonoscopy and artificial intelligence: Bridging the gap or a gap needing to be bridged? Artif Intell Gastrointest Endosc 2021; 2(2): 36-49 [DOI: 10.37126/aige.v2.i2.36] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
23 Sinagra E, Rossi F, Raimondo D. Use of Artificial Intelligence in Endoscopic Training: Is Deskilling a Real Fear? Gastroenterology 2021;160:2212. [PMID: 33417943 DOI: 10.1053/j.gastro.2020.12.065] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
24 Hann A, Troya J, Fitting D. Current status and limitations of artificial intelligence in colonoscopy. United European Gastroenterol J 2021;9:527-33. [PMID: 34617420 DOI: 10.1002/ueg2.12108] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
25 Zhang Y, Zhang X, Wu Q, Gu C, Wang Z. Artificial Intelligence-Aided Colonoscopy for Polyp Detection: A Systematic Review and Meta-Analysis of Randomized Clinical Trials. J Laparoendosc Adv Surg Tech A 2021. [PMID: 33524298 DOI: 10.1089/lap.2020.0777] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
26 Parsa N, Byrne MF. Artificial intelligence for identification and characterization of colonic polyps. Ther Adv Gastrointest Endosc 2021;14:26317745211014698. [PMID: 34263163 DOI: 10.1177/26317745211014698] [Reference Citation Analysis]
27 Antonelli G, Badalamenti M, Hassan C, Repici A. Impact of artificial intelligence on colorectal polyp detection. Best Pract Res Clin Gastroenterol 2021;52-53:101713. [PMID: 34172246 DOI: 10.1016/j.bpg.2020.101713] [Reference Citation Analysis]
28 Repici A, Spadaccini M, Antonelli G, Correale L, Maselli R, Galtieri PA, Pellegatta G, Capogreco A, Milluzzo SM, Lollo G, Di Paolo D, Badalamenti M, Ferrara E, Fugazza A, Carrara S, Anderloni A, Rondonotti E, Amato A, De Gottardi A, Spada C, Radaelli F, Savevski V, Wallace MB, Sharma P, Rösch T, Hassan C. Artificial intelligence and colonoscopy experience: lessons from two randomised trials. Gut 2021:gutjnl-2021-324471. [PMID: 34187845 DOI: 10.1136/gutjnl-2021-324471] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
29 Glissen Brown JR, Waljee AK, Mori Y, Sharma P, Berzin TM. Charting a path forward for clinical research in artificial intelligence and gastroenterology. Dig Endosc 2021. [PMID: 33715244 DOI: 10.1111/den.13974] [Reference Citation Analysis]
30 Joseph J, LePage EM, Cheney CP, Pawa R. Artificial intelligence in colonoscopy. World J Gastroenterol 2021; 27(29): 4802-4817 [PMID: 34447227 DOI: 10.3748/wjg.v27.i29.4802] [Reference Citation Analysis]
31 Rath T. Missed lesions and artificial intelligence during colonoscopy: the tireless working expert in the room. Endoscopy 2021. [PMID: 34905793 DOI: 10.1055/a-1669-8814] [Reference Citation Analysis]