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Updated: Jan 17, 2026

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
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XGBoost机器学习算法用于预测冠状动脉心脏病的老年患者的无计划再入院

Xuewu Song1, Jianyou Shi1, Changyu Zhu1

  • 1Department of Pharmacy, Personalized Drug Research and Therapy Key Laboratory of Sichuan Province, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, China.

Geriatric nursing (New York, N.Y.)
|September 13, 2025
PubMed
概括

这项研究开发了一种极端梯度增强 (XGBoost) 模型,用于预测冠心病 (CHD) 的中国老年患者1年的计划外再入院情况. 关键预测因素包括停留时间和并发症.

关键词:
冠心病是一种冠心病.年长的老人.机器学习 机器学习计划外再接收计划外再接收

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