Gastro hep advances · 2025
Provider Attitudes and Perceptions on Using Artificial Intelligence in Colonoscopy: A Systematic Review and Meta-Analysis.
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Soleymanjahi Saeed, Rajashekar Niroop, Chung Sunny, Grimshaw Alyssa A, Tvedt Mary Jo K, Foroutan Farid, Sultan Shahnaz, Shung Dennis L, Kolb Jennifer M
Аннотация
BACKGROUND AND AIMS: Colonoscopy is the gold standard screening modality for colorectal cancer; however, it is operator-dependent and reliant on exam quality. Incorporating artificial intelligence (AI) into colonoscopy may improve adenoma detection and clinical outcomes, but this is a sociotechnical challenge that requires effective human-AI teaming incorporating provider attitudes.
METHODS: We conducted a systematic review of studies evaluating attitudes and perspectives of providers toward AI-assisted colonoscopy. Participant responses to outcome questions of interest were combined across the studies to calculate pooled proportion (Pp) and 95% confidence interval (CI). Top-ranked perceived advantages and disadvantages in each study were defined as the items that >50% of the study participants voted for.
RESULTS: Out of 2044 abstracts screened, 13 studies were included representing 1538 providers who were mostly gastroenterologists or trainees and 25%-100% had direct experience using AI in a clinical setting. Overall, a large majority were interested in using AI (Pp = 80%, 95% CI 70%-89%, n = 8 studies) and believed it can improve adenoma or polyp detection rate (Pp = 74%, 95% CI 68%-80%, n = 4 studies). Among 5 studies addressing financial implications, about half were concerned about the cost of using AI (52%, 95% CI 24%-79%). An average of 38% of respondents (95% CI 9%-73%) from 4 studies raised concern regarding accountability for misdiagnosis. High number of false positives and an absence of clinical guidelines were top-ranked perceived disadvantages in 2 studies.
CONCLUSION: Most gastroenterology providers expressed interest in using AI systems with colonoscopy and believed it can improve adenoma detection rate. Cost, high number of false positives, and lack of professional society guidelines were among top perceived concerns.
METHODS: We conducted a systematic review of studies evaluating attitudes and perspectives of providers toward AI-assisted colonoscopy. Participant responses to outcome questions of interest were combined across the studies to calculate pooled proportion (Pp) and 95% confidence interval (CI). Top-ranked perceived advantages and disadvantages in each study were defined as the items that >50% of the study participants voted for.
RESULTS: Out of 2044 abstracts screened, 13 studies were included representing 1538 providers who were mostly gastroenterologists or trainees and 25%-100% had direct experience using AI in a clinical setting. Overall, a large majority were interested in using AI (Pp = 80%, 95% CI 70%-89%, n = 8 studies) and believed it can improve adenoma or polyp detection rate (Pp = 74%, 95% CI 68%-80%, n = 4 studies). Among 5 studies addressing financial implications, about half were concerned about the cost of using AI (52%, 95% CI 24%-79%). An average of 38% of respondents (95% CI 9%-73%) from 4 studies raised concern regarding accountability for misdiagnosis. High number of false positives and an absence of clinical guidelines were top-ranked perceived disadvantages in 2 studies.
CONCLUSION: Most gastroenterology providers expressed interest in using AI systems with colonoscopy and believed it can improve adenoma detection rate. Cost, high number of false positives, and lack of professional society guidelines were among top perceived concerns.