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

Machine Learning (2327) Clinical Informatics (1509) Emerging Technologies for Rehabilitation (401) Artificial Intelligence (2480)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77839, first published .
Doctor shows patient heart anatomy on tablet during cardiology consultation.

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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Journals

  1. Makimoto H, Nagai R, Suzuki T. Toward Cardiovascular Digital Twins in Japan. JACC: Asia 2026 View