Machine learning models for prediction of adverse events after percutaneous coronary intervention

Nozomi Niimi, Yasuyuki Shiraishi, Mitsuaki Sawano, Nobuhiro Ikemura, Taku Inohara, Ikuko Ueda, Keiichi Fukuda, Shun Kohsaka

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Fingerprint

Dive into the research topics of 'Machine learning models for prediction of adverse events after percutaneous coronary intervention'. Together they form a unique fingerprint.

Medicine & Life Sciences