Immediate postnatal prediction of death or bronchopulmonary dysplasia among very preterm and very low birth weight infants based on gradient boosting decision trees algorithm: A nationwide database study in Japan

• Kota Yoneda,

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft

  Affiliation Department of Pediatrics, The University of Tokyo Hospital, Tokyo, Japan

  https://orcid.org/0000-0003-1605-5340

  ⨯
• Tomohisa Seki,

  Roles Methodology, Supervision, Writing – review & editing

  Affiliation Department of Healthcare Information Management, The University of Tokyo Hospital, Tokyo, Japan

  ⨯
• Yoshimasa Kawazoe ,

  Roles Methodology, Supervision, Writing – review & editing

  * E-mail: kawazoe@m.u-tokyo.ac.jp

  Affiliations Department of Healthcare Information Management, The University of Tokyo Hospital, Tokyo, Japan, Artificial Intelligence and Digital Twin in Healthcare, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

  https://orcid.org/0000-0002-7277-0827

  ⨯
• Kazuhiko Ohe,

  Roles Resources, Supervision, Writing – review & editing

  Affiliations Department of Healthcare Information Management, The University of Tokyo Hospital, Tokyo, Japan, Department of Biomedical Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

  ⨯
• Naoto Takahashi,

  Roles Supervision, Writing – review & editing

  Affiliation Department of Pediatrics, The University of Tokyo Hospital, Tokyo, Japan

  ⨯
• on behalf of the Neonatal Research Network of Japan

  ¶Membership of the Neonatal Research Network of Japan is provided in the Acknowledgments.

  ⨯