使用大型语言模型开发定制的微笑号码的无码开发:临床医生的实用框架
Hye Won Jun1, Sun Young Ryu2, Tae Keun Yoo1
1Department of Ophthalmology, Hangil Eye Hospital, Incheon, Republic of Korea.
Journal of ophthalmology
|July 23, 2025
概括
聊天GPT-4可以创建定制的nomogram计算器用于小切口镜片提取 (SMILE) 手术使用机构特定的数据,消除了编码专业知识的需要. 这种先进的大型语言模型有助于开发用户友好的工具,用于精确的外科手术规划.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能在医学中的应用
- 手术技术 手术技术
背景情况:
- 由于手术技术和患者数据的差异,定制的诺基图对于小切口镜片提取 (SMILE) 是至关重要的.
- 开发这些名ograms通常需要专门的编码技能和统计软件.
研究的目的:
- 评估使用ChatGPT-4,一个大型语言模型 (LLM) 的可行性,以生成用于SMILE手术的定制名ogram计算器.
- 为了确定ChatGPT-4是否可以进行统计分析,并创建一个功能性的基于Web的计算器,而不需要编程知识.
主要方法:
- 追溯分析了1268个SMILE患者的眼睛,将数据分为训练和验证集.
- 使用ChatGPT-4进行线性回归分析,从手术前数据预测术后折射误差.
- 指示ChatGPT-4生成基于网页的名ogram计算器的HTML代码.
主要成果:
- 聊天GPT-4成功地对SMILE进行了名录回归分析,取得了与R和SPSS相似的结果.
- 与经验方法 (p < 0.001) 相比,开发的名图显示了术后折射误差的优异预测准确性.
- 使用ChatGPT-4提示符创建了一个功能性的网页计算器,不需要手动编码.
结论:
- 聊天GPT-4可以有效地生成统计模型和用户友好的计算器工具,用于SMILE名ograms.
- 临床医生可以利用这个LLM来使用自己的数据创建个性化的名ogram计算器,简化手术规划.
- 这项技术使眼科医生能够方便高效地开发定制的诺摩图工具.
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