基于使用ChatGPT-4的人口和实验室因素,开发一种基于眼风险的新型评分系统
1Department of Biomedical Engineering, Yonsei University, Wonju, South Korea.
Medical & biological engineering & computing
|August 11, 2024
概括
使用ChatGPT-4的新无代码方法开发了一种青光眼风险评分系统. 这种方法成功地创建了一个可与传统方法相比的玻璃眼风险计算器.
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:
- 玻璃眼是全球不可逆转的失明的主要原因.
- 准确的风险评估对于早期检测和干预至关重要.
- 开发预测模型的传统方法可能很复杂,需要专门的编码技能.
研究的目的:
- 使用 ChatGPT-4 的无代码方法开发了一种青光眼风险评分系统.
- 为临床使用创建一个可访问的玻璃眼风险计算器.
- 评估与传统方法相比,无代码开发的系统的性能.
主要方法:
- 使用ChatGPT-4对韩国国家健康和营养检查调查数据进行无代码后勤回归分析.
- 开发了一个基于从模型中获得的几率比率的玻璃眼风险评分系统.
- 使用开发的评分系统创建了一个用户友好的风险计算器工具.
主要成果:
- 通过使用ChatGPT-4成功开发了玻璃眼风险评分系统和计算器,而无需手动编码.
- 无代码系统的预测性能与传统的机器学习方法相美.
- 高风险组 (1-2,3-4,5+分) 的几率比分分别为1.87,2.72和15.36,表明显著的玻璃眼风险.
结论:
- 使用ChatGPT-4的新型无代码方法可以有效地开发眼风险评估工具.
- 这种方法使预测分析民主化,使先进的工具可用于临床青光眼的检测.
- 开发的工具提供了一个实际的解决方案,用于识别高风险患青光眼的个人.
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