Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46840, first published .
Predictive Performance of Machine Learning–Based Models for Poststroke Clinical Outcomes in Comparison With Conventional Prognostic Scores: Multicenter, Hospital-Based Observational Study

Predictive Performance of Machine Learning–Based Models for Poststroke Clinical Outcomes in Comparison With Conventional Prognostic Scores: Multicenter, Hospital-Based Observational Study

Predictive Performance of Machine Learning–Based Models for Poststroke Clinical Outcomes in Comparison With Conventional Prognostic Scores: Multicenter, Hospital-Based Observational Study

Fumi Irie   1, 2 * , MD, PhD ;   Koutarou Matsumoto   3 * , MPH, PhD ;   Ryu Matsuo   1, 2 , MD, PhD ;   Yasunobu Nohara   4 , PhD ;   Yoshinobu Wakisaka   2 , MD, PhD ;   Tetsuro Ago   2, 5 , MD, PhD ;   Naoki Nakashima   6 , MD, PhD ;   Takanari Kitazono   2, 5 , MD, PhD ;   Masahiro Kamouchi   1, 5 , MD, PhD

1 Department of Health Care Administration and Management, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

2 Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

3 Biostatistics Center, Graduate School of Medicine, Kurume University, Kurume, Japan

4 Big Data Science and Technology, Faculty of Advanced Science and Technology, Kumamoto University, Kumamoto, Japan

5 Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

6 Medical Information Center, Kyushu University Hospital, Fukuoka, Japan

*these authors contributed equally

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