March 3, 2026Open Access

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

Key Points

Mortality prediction improved with machine learning models, enhancing early intervention strategies.
Key metric indicates that ML-based assessments can identify high-risk older patients effectively.

Structured PICO

Can machine learning predict 1-year mortality in older patients with heart failure?

Population

Older patients with heart failure

Intervention

Machine learning prediction model

Outcome

1-year mortalityhard clinical

Abstract

This work was supported by research funding of Japanese Society of Cardiovascular Physical Therapy and JSPS KAKENHI Grant Number JP25K02969.

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Discussion

Authors

Kanji Yamada

Nobuyuki Kagiyama

Tomoyuki Morisawa

Journals

SHILAP Revista de lepidopterología

The Lancet Regional Health - Western Pacific

Actions

Institutions

Juntendo University

Kobe City Medical Center General Hospital

The Japanese Society of Gastroenterological Surgery

References and Citations

Connected Papers

Building similarity graph...

Analyzing shared references across papers

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

Key Points

Structured PICO

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

Cite this study