使用FedEYE平台和ChatGPT在近视患者中预测眼内膜镜头,近视患者的前腔室浅,使用FedEYE平台和ChatGPT
Zhanyu Su1, Zhaoxiang Wang2, Shanshan Wang2
1Aier Academy of Ophthalmology, Central South University, Changsha, Hunan, China.
Translational vision science & technology
|October 15, 2025
概括
无密码的人工智能 (AI) 模型有效地预测了前腔深度 (ACD) 浅的患者进行植入式结合镜片 (ICL) 手术的顶. 这些人工智能工具为手术安全性和疗效提供了有希望的进步.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 浅的前腔深度 (ACD) 在可植入结膜透镜 (ICL) 手术中提出了挑战.
- 准确预测手术后的密室是优化手术结果和患者安全的关键.
研究的目的:
- 评估无代码人工智能 (AI) 平台FedEYE和ChatGPT在预测ICL手术中浅层ACD患者的顶方面的有效性.
- 为了比较不同的人工智能模型和数据组合的性能,用于预测金库.
主要方法:
- 进行了一项160只眼睛的回顾性研究,这些眼睛的ACD浅 (<2.8毫米).
- 开发了两个无代码的人工智能模型:一个使用FedEYE的集成神经网络 (INN) 与光连贯断层扫描 (OCT) 图像和检查数据,以及使用内存提示的ChatGPT.
- 这些模型使用多式联络手术前数据进行了训练和验证.
主要成果:
- 在INN模型中,将OCT图像和检查数据结合起来,实现了高精度 (0.875),灵敏度 (0.857),特异性 (0.889) 和AUC (0.873).
- 前腔的角度和球形等效与顶呈正相关;年龄和白色对白色直径呈负相关.
- 在记忆提示后,ChatGPT表现出良好的性能,精度为0.813和AUC为0.865.
结论:
- 像FedEYE和ChatGPT这样的无代码AI工具可以直接开发和部署.
- 这些人工智能模型在预测浅层ACD患者的顶方面表现出令人鼓舞的表现,有助于手术规划.
- 利用人工智能进行密室预测具有显著的临床潜力,可以提高ICL手术的安全性和有效性.
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