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Updated: Jul 19, 2025

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:15

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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基于机器学习的医院长时间住院预测在急诊室:一个梯度增强算法分析算法

Addisu Jember Zeleke1, Pierpaolo Palumbo1, Paolo Tubertini2

  • 1Department of Electrical, Electronic, and Information Engineering Guglielmo Marconi, University of Bologna, Bologna, Italy.

Frontiers in artificial intelligence
|August 17, 2023
PubMed
概括

机器学习模型有效地预测患者的住院时间 (LoS) 和长期住院时间 (PLoS),帮助医疗保健决策. 梯度提升和/XGBoost回归表现为预测分别PLoS和LoS的最佳表现.

关键词:
这是分类分类的分类.紧急情况部门的急救部门.机器学习是机器学习.预测 预测 预测 预测长时间的逗留时间.这是一个回归回归的回归.

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