多模式大语言模型作为评估甲状腺相关眼科病的辅助
Bo Ram Kim1, Joon Yul Choi2, Tae Keun Yoo1
1Department of Ophthalmology, Hangil Eye Hospital, Incheon, South Korea.
Computers in biology and medicine
|May 2, 2025
概括
像ChatGPT-4o这样的多式人工智能聊天机器人在使用临床活动得分 (CAS) 评估甲状腺相关眼病 (TAO) 中显示出高准确性,优于CNN模型,并为眼科提供了实用工具.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 甲状腺相关的眼科医疗 (TAO) 需要准确的评估,以有效管理.
- 临床活动评分 (CAS) 是TAO活动的一个关键指标.
- 当前的评估方法可能是耗时和主观的.
研究的目的:
- 评估多式人工智能的有效性,特别是ChatGPT-4o,通过CAS评估TAO.
- 将人工智能驱动的CAS估计与眼科医生和CNN模型性能进行比较.
- 探索AI在生成可访问的TAO评估工具方面的潜力.
主要方法:
- 聊天GPT-4o使用公开可用的案例报告和数据集进行TAO评估.
- 人工智能聊天机器人从文本和眼镜照片中估计了CAS.
- 人工智能预测与眼科医生评估和ResNet50 CNN模型进行了对比.
- 在曲线 (AUCs) 下的接收器操作特征 (ROC) 区域被计算为活性TAO (CAS ≥3).
主要成果:
- 与眼科医生相比,ChatGPT-4o在CAS估计中表现出高准确度,平均绝对误差低 (0.39-0.45).
- 在识别活性TAO方面,AI显著超过ResNet50,实现ROC-AUC为0.974 (手术前) 和0.990 (治疗前).
- 聊天GPT-4o成功生成了一个用户友好的CAS计算器,并为其评估提供了详细的解释.
结论:
- 多模式AI聊天机器人,以ChatGPT-4o为例,为TAO评估提供了可靠和准确的工具.
- 在TAO活动识别和CAS估计方面,ChatGPT-4o超过了传统的CNN模型.
- 人工智能能够创建像CAS计算器这样的实用工具,这突显了它在临床眼科中的重要实用性.
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