Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions

Colonoscopy

Current status and limitations of artificial intelligence in colonoscopy

United European Gastroenterol J

Hann A, Troya J, Fitting D

doi: 10.1002/ueg2.12108

ColonoscopyGastrointestinal Cancer

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study

Lancet Gastroenterol Hepatol.

Wang P, Liu X, Berzin TM, Glissen Brown JR, Liu P, Zhou C, Lei L, Li L, Guo Z, Lei S, Xiong F, Wang H, Song Y, Pan Y, Zhou G

doi: 10.1016/S2468-1253(19)30411-X.

Colonoscopy

Post-colonoscopy Appendicitis - Systematic Review of Current Evidence

J Gastroenterol Hepatol.

Ng ZQ, Elsabagh A, Wijesuriya R

doi: 10.1111/jgh.15130.

Colonoscopy

Artificial Intelligence for Polyp Detection during Colonoscopy: A Systematic Review and Meta-Analysis

Endoscopy.

Barua I, Vinsard D, Jodal H, Løberg M, Kalager M, Holme Ø, Misawa M, Bretthauer M, Mori Y

doi: 10.1055/a-1201-7165.

ColonoscopyGastrointestinal Cancer

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial

Gastroenterology.

Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C

doi: 10.1053/j.gastro.2020.04.062.

ColonoscopyGastrointestinal Cancer

DEEP LEARNING COMPUTER-AIDED POLYP DETECTION REDUCES ADENOMA MISS RATE: A U.S. MULTI-CENTER RANDOMIZED TANDEM COLONOSCOPY STUDY (CADeT-CS Trial)

Clin Gastroenterol Hepatol

Glissen Brown JR, Mansour NM, Wang P, Chuchuca MA, Minchenberg SB, Chandnani M, Liu L, Gross SA, Sengupta N, Berzin TM

doi: 10.1016/j.cgh.2021.09.009

ColonoscopyGastrointestinal Cancer

High-Risk Adenomas at Screening Colonoscopy Remain Predictive of Future High-Risk Adenomas Despite an Intervening Negative Colonoscopy

Am J Gastroenterol.

Sullivan BA, Redding TS 4th, Hauser ER, Gellad ZF, Qin X, Gupta S, Robertson DJ, Weiss DG, OʼLeary MC, Madison AN, Sims KJ, Williams CD, Hong JC, Lieberman D, Provenzale D

doi: 10.14309/ajg.0000000000000677.

Further Publications

Computer-aided detection versus advanced imaging for detection of colorectal neoplasia: a systematic review and network meta-analysis

Lancet Gastroenterol Hepatol

Spadaccini M, Iannone A, Maselli R, Badalamenti M, Desai M, Chandrasekar VT, Patel HK, Fugazza A, Pellegatta G, Galtieri PA, Lollo G, Carrara S, Anderloni A, Rex DK, Savevski V, Wallace MB, Bhandari P, Roesch T, Gralnek IM, Sharma P, Hassan C, Repici A

doi: 10.1016/S2468-1253(21)00215-6

Accurate Classification of Diminutive Colorectal Polyps Using Computer-aided Analysis

Gastroenterology.

Chen PJ, Lin MC, Lai MJ, Lin JC, Lu HH, Tseng VS

doi: 10.1053/j.gastro.2017.10.010.

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Current status and limitations of artificial intelligence in colonoscopy

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study

Post-colonoscopy Appendicitis - Systematic Review of Current Evidence

Artificial Intelligence for Polyp Detection during Colonoscopy: A Systematic Review and Meta-Analysis

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DEEP LEARNING COMPUTER-AIDED POLYP DETECTION REDUCES ADENOMA MISS RATE: A U.S. MULTI-CENTER RANDOMIZED TANDEM COLONOSCOPY STUDY (CADeT-CS Trial)

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Accurate Classification of Diminutive Colorectal Polyps Using Computer-aided Analysis