Yousaf Muhammad N, Sharma Neal, Matteson-Kome Michelle L, Puli Srinivas, Nguyen Douglas, Bechtold Matthew L
Department of Medicine/Gastroenterology and Hepatology, University of Missouri School of Medicine and University Hospital, Columbia, USA.
Department of Gastroenterology and Hepatology, Digestive Health Specialists, P.A., Winston-Salem, USA.
Cureus. 2024 Nov 27;16(11):e74600. doi: 10.7759/cureus.74600. eCollection 2024 Nov.
Background Artificial intelligence (AI) is a hot topic in the world of medicine. AI may be useful in identifying and sizing polyps, which influence surveillance intervals. Therefore, we examined polyp size estimation by AI using a survey study. Methods A survey study was performed using a phantom colon model. Eleven videos were produced in the colon phantom using a colonoscope. Gastroenterologists were compared to a new AI system (Argus) for sizing polyps and their impact on surveillance intervals. Results Eleven gastroenterologists completed the survey with a mean age of 51.1 ± 8.1 years and an average of 19.3 ± 10 years of experience. Mean accuracy rates for gastroenterologists were 76% ± 0.1% (range 54-89%) compared to 96% ± 0.05% for Argus. Endoscopists estimated polyp size within ± 1 mm 44 times (36%) versus 9 times (82%) with Argus. Endoscopists' surveillance recommendations were significantly more often inappropriate compared to Argus (34 vs 0). The interval of next colonoscopy was too short for 27 endoscopists (22%) and too long for seven endoscopists (6%). Conclusions AI appears to be more accurate in estimating polyp size than experienced endoscopists. Given the potential impact on surveillance intervals, AI may result in cost savings.
背景 人工智能（AI）是医学领域的一个热门话题。人工智能在识别息肉及确定其大小方面可能有用，而息肉大小会影响监测间隔。因此，我们通过一项调查研究来检验人工智能对息肉大小的估计。方法 使用模拟结肠模型进行一项调查研究。用结肠镜在结肠模拟物中生成11个视频。将胃肠病学家与一种新的人工智能系统（阿格斯）在息肉大小测定及其对监测间隔的影响方面进行比较。结果 11名胃肠病学家完成了调查，他们的平均年龄为51.1±8.1岁，平均从业经验为19.3±10年。胃肠病学家的平均准确率为76%±0.1%（范围为54 - 89%），而阿格斯的准确率为96%±0.05%。内镜医师估计息肉大小在±1毫米范围内的有44次（36%），而阿格斯为9次（82%）。与阿格斯相比，内镜医师的监测建议明显更常不合适（34次对0次）。27名内镜医师（22%）建议的下一次结肠镜检查间隔太短，7名内镜医师（6%）建议的间隔太长。结论 在估计息肉大小方面，人工智能似乎比经验丰富的内镜医师更准确。鉴于对监测间隔的潜在影响，人工智能可能会节省成本。
