Risk Stratification and Outcome Prediction in Heart Failure Patients With Cardiac Implantable Electronic Devices Using Machine Learning Analysis From the HINODE Study

Interpretable ML provided accurate risk prediction and phenotype-based stratification in Japanese HF patients with cardiac devices, supporting personalized management.

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Publication Details

Journal
Circulation Reports
Published
2025-11-28
DOI
https://doi.org/10.1253/circrep.cr-25-0204
Primary Topic
Cardiac pacing and defibrillation studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

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article

Risk Stratification and Outcome Prediction in Heart Failure Patients With Cardiac Implantable Electronic Devices Using Machine Learning Analysis From the HINODE Study

Circulation Reports
Cardiac pacing and defibrillation studies
article

Risk Stratification and Outcome Prediction in Heart Failure Patients With Cardiac Implantable Electronic Devices Using Machine Learning Analysis From the HINODE Study

article en

Abstract

Interpretable ML provided accurate risk prediction and phenotype-based stratification in Japanese HF patients with cardiac devices, supporting personalized management.

Circulation ReportsVol. 8(2)
Toho University (JP), University of Tsukuba (JP), Toho University Ohashi Medical Center (JP), Boston Scientific (Netherlands) (NL)
Boston Scientific Corporation
Good health and well-being
Openalex Percentile: Top 34%
Cardiac pacing and defibrillation studies
DOIOpen Access PDFOpenAlex
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