基于机器学习的算法,用于预测人工肝治疗的肝衰竭患者的90天生存率
Bo Deng1,2, Chengzhi Bai1, Huaqian Xu1
1Department of Gastroenterology, The General Hospital of Western Theater Command, Chengdu, Sichuan, China.
Frontiers in physiology
|November 12, 2025
概括
机器学习模型可以预测人工肝治疗的肝衰竭患者的90天生存期. 后勤回归证明了最高的准确性,有助于个性化的预后评估,以获得更好的患者结果.
科学领域:
- 肝病学和人工器官支持
- 机器学习在医学中的应用
- 预测模型的预测建模
背景情况:
- 肝衰竭带有很高的短期死亡风险.
- 预测人工肝支持患者的结果具有挑战性.
- 确定可靠的预后因素对于患者管理至关重要.
研究的目的:
- 开发和验证用于预测90天生存期的机器学习模型.
- 确定肝衰竭患者生存的关键临床预测因素.
- 评估人造肝脏支持系统在预测患者结果方面的实用性.
主要方法:
- 对接受人工肝治疗的197名肝衰竭患者的回顾性分析.
- 使用LASSO回归和后勤回归进行特征选择.
- 使用后勤回归,随机森林,SVM,XGBoost和KNN的模型开发.
- 使用AUC,精度,灵敏度和特异性的性能评估.
主要成果:
- 逻辑回归 (LR) 实现了最高的预测性能 (AUC = 0.884,精度 = 75.0%).
- 确定的关键独立预测因素包括年龄,直接胆红素,视网醇,α-胎蛋白和血栓时间.
- 使用纵向数据的LR模型也显示出强大的预测能力 (AUC为0.869和0.859).
结论:
- 机器学习模型对预测肝功能衰竭患者的生存有希望.
- 这些模型可以支持个性化的预后评估.
- 通过机器学习,可以更好地预测人工肝支持治疗结果.
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