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Shun Kohsaka

Keio University - Department of Cardiology

Tokyo

Japan

  • Keio University - Department of Cardiology

SCHOLARLY PAPERS

2

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106

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Scholarly Papers (2)

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1.

Machine Learning-Based Models Did Not Improve the Prediction of Complications after Percutaneous Coronary Intervention in Japan

Number of pages: 25 Posted: 01 Jun 2021
Nozomi Niimi, Yasuyuki Shiraishi, Mitsuaki Sawano, Nobuhiro Ikemura, Taku Inohara, Ikuko Ueda, Keiichi Fukuda and Shun Kohsaka
Keio University - Department of Cardiology, Keio University - Department of Cardiology, Tokyo Dental College - Department of Cardiology, Keio University - Department of Cardiology, Keio University - Department of Cardiology, Keio University - Department of Cardiology, Keio University - Department of Cardiology and Keio University - Department of Cardiology
Downloads 62 (942,565)

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2.

Assessment of Thromboembolism Risk in COVID-19 Patients with Cardiovascular Disease Risk Factors: Analysis from the Japanese Nationwide Registry

Number of pages: 17 Posted: 10 Mar 2022
Eiji Shibahashi, Kentaro Jujo, Shunsuke Kuroda, Shingo Matsumoto, Takahide Sano, Takeshi Kitai, Taishi Yonetsu, Shun Kohsaka, Sho Torii, Tetsuo Yamaguchi, Takuya Kishi, Issei Komuro, Ken-ichi Hirata, Koichi Node and Yuya Matsue
affiliation not provided to SSRN, Tokyo Women's Medical University - Department of Cardiology, Cleveland Clinic - Section of Cardiac Pacing and Electrophysiology, Toho University, affiliation not provided to SSRN, National Cerebral and Cardiovascular Centre, affiliation not provided to SSRN, Keio University - Department of Cardiology, affiliation not provided to SSRN, Toranomon Hospital, affiliation not provided to SSRN, affiliation not provided to SSRN, Kobe University, Saga University - Department of Cardiovascular Medicine and Juntendo University - Graduate School of Medicine
Downloads 44 (1,133,231)

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Coronavirus disease-2019, Cardiovascular disease risk factors, Thromboembolism, In-hospital mortality, Prediction model