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

Machine Learning (2100) Artificial Intelligence (2168) Emerging Technologies for Rehabilitation (356) Clinical Informatics (1339)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77839, first published .
Predicting Left Ventricular Ejection Fraction Recovery After Percutaneous Coronary Intervention in Patients With Chronic Coronary Syndrome by Using Interpretable Machine Learning Models: Retrospective Study

Predicting Left Ventricular Ejection Fraction Recovery After Percutaneous Coronary Intervention in Patients With Chronic Coronary Syndrome by Using Interpretable Machine Learning Models: Retrospective Study

Predicting Left Ventricular Ejection Fraction Recovery After Percutaneous Coronary Intervention in Patients With Chronic Coronary Syndrome by Using Interpretable Machine Learning Models: Retrospective Study

Authors of this article:

Jiayi Ding1 Author Orcid Image ;   Guanqi Lyu1 Author Orcid Image ;   Masaharu Nakayama1 Author Orcid Image ;   Kotaro Nochioka2 Author Orcid Image ;   Jun Takahashi2 Author Orcid Image ;   Satoshi Yasuda2 Author Orcid Image ;   Tetsuya Matoba3 Author Orcid Image ;   Takahide Kohro4 Author Orcid Image ;   Naoyuki Akashi5 Author Orcid Image ;   Hideo Fujita5 Author Orcid Image ;   Yusuke Oba6 Author Orcid Image ;   Tomoyuki Kabutoya6 Author Orcid Image ;   Kazuomi Kario6 Author Orcid Image ;   Yasushi Imai7 Author Orcid Image ;   Arihiro Kiyosue8 Author Orcid Image ;   Yoshiko Mizuno9 Author Orcid Image ;   Takamasa Iwai10 Author Orcid Image ;   Yoshihiro Miyamoto11 Author Orcid Image ;   Masanobu Ishii12 Author Orcid Image ;   Kenichi Tsujita12 Author Orcid Image ;   Taishi Nakamura13 Author Orcid Image ;   Hisahiko Sato14 Author Orcid Image ;   Ryozo Nagai15 Author Orcid Image
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