改善诊断:在性结肠炎内镜评估中,ChatGPT-4的性能.
Asaf Levartovsky1, Ahmad Albshesh1, Ana Grinman1
1Gastroenterology, affiliated with Tel Aviv University, Sheba Medical Center, Tel Hashomer, Israel.
聊天GPT-4在使用Mayo Endoscopic Subscore对性结肠炎内镜图像进行分级方面表现出潜力,其准确性与炎症性肠病专家相美.
科学领域:
- 胃肠病学 胃肠病学
- 人工智能在医学中的应用
- 医学成像分析 医学成像分析
背景情况:
- 梅奥内镜子评分 (MES) 对于评估性结肠炎 (UC) 活动至关重要.
- 人工智能 (AI) 具有提高诊断准确度和减少内镜中观察者之间的变异性的潜力.
- 这项研究研究了ChatGPT-4在UC中MES分级的实用性.
研究的目的:
- 评估ChatGPT-4在使用MES的UC患者内镜图像分级的诊断准确性.
- 为了比较ChatGPT-4的性能与专家共识和炎症性肠病 (IBD) 专家.
主要方法:
- 专家共识通过使用MES对现实世界UC内镜图像进行了分级.
- 三名IBD专家和ChatGPT-4评估了均分级的图像.
- 将ChatGPT-4和IBD专家分级与专家共识进行了比较.
主要成果:
- 在50张图像中,有30张图像获得了统一的专家评分.
- 与共识板相比,ChatGPT-4的平均准确率达到78.9%.
- IBD专家的平均准确率为81.1%,与ChatGPT-4 (P=0.71) 没有显著差异.
结论:
- 聊天GPT-4显示了从内镜图像评估UC粘膜炎症严重程度的潜力.
- 人工智能模型的性能与IBD专家相比,没有具体的微调.
- 这表明AI在支持UC内镜评估中的作用.
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