Soleymanjahi Saeed, Rajashekar Niroop, Chung Sunny, Grimshaw Alyssa A, Tvedt Mary Jo K, Foroutan Farid, Sultan Shahnaz, Shung Dennis L, Kolb Jennifer M
Division of Gastroenterology, Mass General Brigham, Harvard School of Medicine, Boston, Massachusetts.
Department of Medicine, Yale School of Medicine, New Haven, Connecticut.
Gastro Hep Adv. 2025 Jul 11;4(10):100746. doi: 10.1016/j.gastha.2025.100746. eCollection 2025.
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.
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.
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.
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.
结肠镜检查是结直肠癌的金标准筛查方式;然而,它依赖于操作人员,且取决于检查质量。将人工智能(AI)应用于结肠镜检查可能会提高腺瘤检测率及改善临床结果,但这是一项社会技术挑战,需要有效的人机协作,同时考虑医疗服务提供者的态度。
我们对评估医疗服务提供者对人工智能辅助结肠镜检查的态度和观点的研究进行了系统综述。将各研究中参与者对感兴趣的结果问题的回答进行汇总,以计算合并比例(Pp)和95%置信区间(CI)。每项研究中排名靠前的感知优势和劣势被定义为超过50%的研究参与者投票支持的项目。
在筛选的2044篇摘要中,纳入了13项研究,涉及1538名医疗服务提供者,他们大多是胃肠病学家或实习生,25%-100%的人在临床环境中直接使用过人工智能。总体而言,绝大多数人对使用人工智能感兴趣(Pp = 80%,95% CI 70%-89%,n = 8项研究),并认为它可以提高腺瘤或息肉检测率(Pp = 74%,95% CI 68%-80%,n = 4项研究)。在涉及财务影响的5项研究中,约一半人担心使用人工智能的成本(52%,95% CI 24%-79%)。4项研究中平均38%的受访者(95% CI 9%-73%)对误诊的责任表示担忧。在2项研究中,高假阳性率和缺乏临床指南是排名靠前的感知劣势。
大多数胃肠病学医疗服务提供者表示有兴趣在结肠镜检查中使用人工智能系统,并认为它可以提高腺瘤检测率。成本、高假阳性率和缺乏专业协会指南是最受关注的问题。