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Open Access
Peer-reviewed
Research Article
Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy
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Minoru Sakuragi,
Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft
Affiliations Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan, Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Eiichiro Uchino,
Roles Data curation, Methodology, Software, Writing – review & editing
Affiliations Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan, Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Noriaki Sato,
Roles Data curation, Methodology, Writing – review & editing
Affiliations Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan, Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Takeshi Matsubara,
Roles Validation, Writing – review & editing
Affiliation Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Akihiko Ueda,
Roles Validation, Writing – review & editing
Affiliations Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan, Department of Gynecology and Obstetrics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Yohei Mineharu,
Roles Validation, Writing – review & editing
Affiliations Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan, Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan, Department of Artificial Intelligence in Healthcare and Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Ryosuke Kojima,
Roles Software
Affiliation Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Motoko Yanagita ,
Roles Project administration, Resources, Supervision, Writing – review & editing
* E-mail: okuno.yasushi.4c@kyoto-u.ac.jp (YO); motoy@kuhp.kyoto-u.ac.jp (MY)
Affiliations Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan, Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan
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Yasushi Okuno
Roles Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing
* E-mail: okuno.yasushi.4c@kyoto-u.ac.jp (YO); motoy@kuhp.kyoto-u.ac.jp (MY)
Affiliation Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy
- Minoru Sakuragi,
- Eiichiro Uchino,
- Noriaki Sato,
- Takeshi Matsubara,
- Akihiko Ueda,
- Yohei Mineharu,
- Ryosuke Kojima,
- Motoko Yanagita,
- Yasushi Okuno
- Published: March 19, 2024
- https://doi.org/10.1371/journal.pone.0298673