Larsen Solveig Linnea Veen, Mori Yuichi
Clinical Effectiveness Research Group, Institute of Health and Society, University of Oslo Oslo Norway.
Department of Transplantation Medicine, Oslo University Hospital University of Oslo Oslo Norway.
DEN Open. 2022 Mar 23;2(1):e109. doi: 10.1002/deo2.109. eCollection 2022 Apr.
Artificial intelligence has become an increasingly hot topic in the last several years, and it has also gained its way into the medical field. In recent years, the application of artificial intelligence in the gastroenterology field has been of increasing interest, particularly in the colonoscopy setting. Novel technologies such as deep neural networks have enabled real-time computer-aided polyp detection and diagnosis during colonoscopy. This might lead to increased performance of endoscopists as well as potentially reducing the costs of unnecessary polypectomies of hyperplastic polyps. Newly published prospective trials studying computer-aided detection showed that the assistance of artificial intelligence significantly increased the detection of polyps and non-advanced adenomas approximately by 10%, while three tandem randomized control trials proved that the adenoma miss rate was significantly reduced (e.g., 13.8% vs. 36.7% in one Japanese multicenter trial). Promising results have also been shown in prospective single-arm trials on computer-aided polyp diagnosis, but the evidence is insufficient to reach a conclusion.
在过去几年里，人工智能已成为一个日益热门的话题，并且它也已进入医学领域。近年来，人工智能在胃肠病学领域的应用越来越受到关注，尤其是在结肠镜检查方面。诸如深度神经网络等新技术已能够在结肠镜检查期间进行实时计算机辅助息肉检测和诊断。这可能会提高内镜医师的工作效率，并有可能降低增生性息肉不必要息肉切除术的成本。新发表的研究计算机辅助检测的前瞻性试验表明，人工智能的辅助显著提高了息肉和非高级别腺瘤的检测率，大约提高了10%，而三项串联随机对照试验证明腺瘤漏诊率显著降低（例如，在一项日本多中心试验中为13.8%对36.7%）。在计算机辅助息肉诊断的前瞻性单臂试验中也显示出了有前景的结果，但证据不足以得出结论。
