用CURATE进行人工智能辅助的华法林剂量优化.AI对临床影响:回顾性数据分析
Tiffany Rui Xuan Gan1, Lester W J Tan2,3,4, Mathias Egermark2,3,4
1Division of Surgery Ng Teng Fong General Hospital Singapore Singapore.
Bioengineering & translational medicine
|May 19, 2025
概括
人工智能 (AI) 可以优化华法林剂量,提高准确性并降低风险. 与现有模型相比,CURATE.AI 显示出优异的预测误差和可以忽略不计的低预测偏差.
科学领域:
- 药物基因组学 药物基因组学
- 人工智能在医学中的应用
- 临床决策支持系统 临床决策支持系统
背景情况:
- 标准的华法林剂量依赖于医生的指导,往往导致国际规范化比率 (INR) 控制不足.
- 华法林反应的患者间和患者内变异可能导致诸如出血或血栓形成等不良事件.
研究的目的:
- 评估CURATE.AI,一个AI平台,以优化华法林剂量定位.
- 将CURATE.AI的性能与现有模型和医生指导的剂量进行比较.
主要方法:
- 使用患者的华法林剂量和INR变化,创建了一个个性化的CURATE.AI响应概况.
- 使用百分比绝对预测错误和百分比预测错误等指标评估了CURATE.AI的预测性能.
- 对127名患者的数据进行了追溯分析.
主要成果:
- 与其他模型相比,CURATE.AI显示出更好的预测准确性 (较低的百分比绝对预测误差和百分比预测误差为20%).
- 人工智能证明了微不足道的预测偏差,可能降低出血风险.
- 使用CURATE.AI的治疗范围中的建模时间与医生指导的剂量相比较.
结论:
- CURATE.AI提供了对华法林剂量的系统方法,减少了医生猜测.
- 这种人工智能平台可以支持有效使用华法林,从而避免昂贵的新型抗凝固剂.
- 需要进一步的前性研究来确定CURATE.AI作为临床决策支持工具.
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