[基于XGBoost算法的机器学习模型在急性严重胰腺炎患者早期预测中的应用]
Xin Gao1, Jiaxi Lin1, Airong Wu1
1Department of Gastroenterology, the First Affiliated Hospital of Soochow University, Suzhou Digestive Disease Clinical Medical Center, Suzhou 215006, Jiangsu, China.
这项研究开发了一种XGBoost机器学习模型,用于早期预测严重急性胰腺炎 (SAP). 该模型在入院后48小时内识别SAP风险具有很高的准确性,优于传统评分系统.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的机器学习
- 胃肠病学 胃肠病学
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