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Updated: Jul 12, 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

Published on: June 10, 2025

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机器学习模型中的可解释性价格对于心力衰竭的100天再入诊预测:回顾性,比较性,机器学习研究

Amira Soliman1, Björn Agvall2,3, Kobra Etminani1,2

  • 1Center for Applied Intelligent Systems Research, School of Information Technology, Halmstad University, Halmstad, Sweden.

Journal of medical Internet research
|October 27, 2023
PubMed
概括

可解释的机器学习 (ML) 模型对于预测心力衰竭 (HF) 再入院是有效的. 一个传统的,可解释的ML模型的性能与深度学习相提并论,为患者护理提供了可操作的见解.

关键词:
深度学习是一种深度学习.可解释的人工智能心脏衰竭是因为心脏衰竭.机器学习是机器学习.再接收预测 预测 再接收浅层学习是一种浅层的学习.

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