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A. Cassinotti, Valentina Zadro, Matteo Ferraris, Marco Parravicini, Thomas P. Chapman, Stefano La Rosa, Sergio Segato
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Advanced imaging for detection and differentiation of colorectal neoplasia. ESGE guideline–update 2019
10.1055/a-1031-7657 · 2019
SCENIC Guideline Development Panel. SCENIC international consensus statement on surveillance and management of dysplasia in inflammatory bowel disease
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ECCO topical review optimising reporting in surgery, endoscopy and histopatology
10.1093/ecco-jcc/jjab011 · 2021
Endoscopic characterization of neoplastic and non-neoplastic lesions in inflammatory bowel disease: Systematic review in the era of advanced endoscopic imaging
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Colorectal tumours and pit pattern
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Endoscopic prediction of deep submucosal invasive carcinoma: Validation of the narrow-band imaging international colorectal endoscopic (NICE) classification
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Modified Kudo classification can improve accuracy of virtual chromoendoscopy with FICE in endoscopic surveillance of ulcerative colitis
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Impact of artificial intelligence on miss rate of colorectal neoplasia
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Development of an artificial intelligence tool for detecting colorectal lesions in inflammatory bowel disease
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A pilot evaluation of the artificial intelligence system CAD-EYE to optically characterise lesions in inflammatory bowel disease surveillance
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Low interobserver agreement among endoscopists in differentiating dysplastic from non-dysplastic lesions during inflammatory bowel disease colitis surveillance
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Prospective, randomized, back-to-back trial evaluating the usefulness of i-SCAN in screening colonoscopy
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Low interobserver agreement among endoscopists in differentiating dysplastic from non-dysplastic lesions during inflammatory bowel disease colitis surveillance
10.3109/00365521.2015.1016449 · doi-reference
A pilot evaluation of the artificial intelligence system CAD-EYE to optically characterise lesions in inflammatory bowel disease surveillance
10.1177/26317745251363517 · doi-reference
Computer-aided detection colonoscopy for surveillance in IBD patients: Insights from a single-center experience
10.1093/ibd/izaf180 · doi-reference
Development of an artificial intelligence tool for detecting colorectal lesions in inflammatory bowel disease
10.1016/j.igie.2023.03.004 · doi-reference
The diagnostic ability to classify neoplasia occurring in inflammatory bowel disease by artificial intelligence and endoscopists: A pilot study
10.1111/jgh.15904 · doi-reference
New AI model for neoplasia detection and characterization in inflammatory bowel disease
10.1136/gutjnl-2023-330718 · doi-reference
Definition of competence standards for optical diagnosis of diminutive colorectal polyps: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement
10.1055/a-1689-5130 · doi-reference
Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: A multicenter randomized controlled trial
10.1007/s00535-021-01808-w · doi-reference
Impact of artificial intelligence on miss rate of colorectal neoplasia
10.1053/j.gastro.2022.03.007 · doi-reference
Deep learning computer-aided polyp detection reduces adenoma miss rate: A United States multi-center randomized tandem colonoscopy study (CADeT-CS Trial)
10.1016/j.cgh.2021.09.009 · doi-reference
Comparison of linked color imaging and white-light colonoscopy for detection of colorectal polyps: A multicenter, randomized, crossover trial
10.1016/j.gie.2017.02.035 · doi-reference
The 2019 World Health Organization Classification of appendiceal, colorectal and anal canal tumours: An update and critical assessment
10.1016/j.pathol.2020.10.010 · doi-reference
Improvement in the visibility of colorectal polyps by using blue laser imaging (with video)
10.1016/j.gie.2015.01.030 · doi-reference
Polyp miss rate determined by tandem colonoscopy: A systematic review
10.1111/j.1572-0241.2006.00390.x · doi-reference
Colonoscopic miss rates of adenomas determined by back-to-back colonoscopies
10.1016/s0016-5085(97)70214-2 · doi-reference
STARD 2015: An updated list of essential items for reporting diagnostic accuracy studies
10.1136/bmj.h5527 · doi-reference
Blue laser imaging, blue light imaging, and linked color imaging for the detection and characterization of colorectal tumors
10.5009/gnl18276 · doi-reference
10.1371/journal.pone.0255955
10.1371/journal.pone.0255955 · doi-reference
Artificial intelligence-assisted optical diagnosis for the resect-and-discard strategy in clinical practice: The Artificial intelligence BLI Characterization (ABC) study
10.1055/a-1852-0330 · doi-reference
Accuracy of optical diagnosis with narrow band imaging in the surveillance of ulcerative colitis: A prospective study comparing Kudo, Kudo-IBD and NICE classifications
10.1007/s00384-024-04635-6 · doi-reference
Virtual chromoendoscopy with FICE for the classification of polypoid and non polypoid raised lesions in ulcerative colitis
10.1097/mcg.0000000000000974 · doi-reference
Endoscopic prediction of deep submucosal invasive carcinoma: Validation of the narrow-band imaging international colorectal endoscopic (NICE) classification
10.1016/j.gie.2013.04.185 · doi-reference
Colorectal tumours and pit pattern
10.1136/jcp.47.10.880 · doi-reference
Endoscopic characterization of neoplastic and non-neoplastic lesions in inflammatory bowel disease: Systematic review in the era of advanced endoscopic imaging
10.1177/17562848231208667 · doi-reference
ECCO topical review optimising reporting in surgery, endoscopy and histopatology
10.1093/ecco-jcc/jjab011 · doi-reference
SCENIC Guideline Development Panel. SCENIC international consensus statement on surveillance and management of dysplasia in inflammatory bowel disease
10.1053/j.gastro.2015.01.031 · doi-reference
Advanced imaging for detection and differentiation of colorectal neoplasia. ESGE guideline–update 2019
10.1055/a-1031-7657 · doi-reference