评估ChatGPT-4用于解读几种诊断技术中的胃肠病学图像
Miguel Mascarenhas Saraiva1,2,3, Tiago Ribeiro1,2,3, Belén Agudo4
1Precision Medicine Unit, Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
Journal of clinical medicine
|January 25, 2025
概括
在解释囊内镜和内镜超声波等手术中的胃肠道图像方面,ChatGPT-4的准确性有限. 在临床使用这种人工智能工具之前,需要进一步改进.
科学领域:
- 胃肠病学 胃肠病学
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 大型语言模型 (LLM) 越来越多地集成到临床环境中.
- 最近的LLM版本具有图像分析功能,但它们在胃肠病学中的诊断性能基本上没有被评估.
- 这项研究评估了ChatGPT-4在解释各种胃肠病相关医疗图像方面的有效性.
研究的目的:
- 评估ChatGPT-4在解释来自五个关键胃肠病学程序的医疗图像中的诊断性能.
- 为了比较ChatGPT-4的图像解释精度与黄金标准诊断.
主要方法:
- 分析了740张囊内镜 (CE),设备辅助肠镜 (DAE),内镜超声波 (EUS),数字单操作员胆管镜 (DSOC) 和高分辨率无光镜 (HRA) 的图像.
- 聊天GPT-4使用预定义提示解读图像.
- 使用准确度,灵敏度,特异性,正预测值 (PPV),负预测值 (NPV) 和曲线下的面积 (AUC) 来评估性能.
主要成果:
- 聊天GPT-4实现了CE的准确率为50.0%,CE的准确率为90.0%,DAE的准确率为67.0%.
- 对于EUS,胰腺囊的AUC为0.488,固体病变的AUC为0.550,区分胆道狭窄的AUC为0.550.
- 对HRA的整体准确度在47.5%至67.5%之间.
结论:
- 在多种胃肠病学成像技术中,ChatGPT-4显示出低于最佳的诊断准确性.
- 人工智能模型在胃肠病学图像解释中广泛采用临床应用之前需要显著改进.
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