Temporal trends in myocardial ischemia risk estimated from 12-lead electrocardiograms using deep learning in individuals with suspected cancer during health checkups
Ken Kurisu·Yosuke Uchitomi·Kyoko Ito·Akira Fukui·Kazuhiro Yoshiuchi·Maiko Fujimori·Tatsuo Akechi·Tomohiro Kato·Kohei Takeshita
Previous studies have suggested the potential effect of psychological stress related to cancer diagnosis on cardiovascular mortality. This study aimed to investigate the temporal trends of cardiovascular risk before and after cancer diagnosis using a deep learning model applied to 12-lead electrocardiograms (ECGs). We developed a deep learning model using a publicly available large-scale dataset to quantify myocardial ischemia risk from 12-lead ECGs. We collected ECG records from individuals dia