This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1448) Data Science (342) Nephrology/Renal Disorders (90) Cardiac Diagnostics (26) Cardiac Arrhythmia, Atrial Fibrillation (112) Machine Learning (1933)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73353, first published .
Cardiorenal Interorgan Assessment via a Novel Clustering Method Using Dynamic Time Warping on Electrocardiogram: Model Development and Validation Study

Cardiorenal Interorgan Assessment via a Novel Clustering Method Using Dynamic Time Warping on Electrocardiogram: Model Development and Validation Study

Cardiorenal Interorgan Assessment via a Novel Clustering Method Using Dynamic Time Warping on Electrocardiogram: Model Development and Validation Study

Authors of this article:

Sally Zhao1 Author Orcid Image ;   Zhan Ye2 Author Orcid Image ;   Bhavna Adhin3 Author Orcid Image ;   Matti Vuori4, 5 Author Orcid Image ;   Jari Laukkanen6, 7 Author Orcid Image ;   FinnGen 8 ;   Sudeshna Fisch2 Author Orcid Image
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