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Development and Validation of a Prognostic Classification Model Predicting Postoperative Adverse Outcomes in Older Surgical Patients Using a Machine Learning Algorithm: Retrospective Observational Network Study.
Choi, Jung-Yeon; Yoo, Sooyoung; Song, Wongeun; Kim, Seok; Baek, Hyunyoung; Lee, Jun Suh; Yoon, Yoo-Seok; Yoon, Seonghae; Lee, Hae-Young; Kim, Kwang-Il.
Afiliação
  • Choi JY; Departmentof Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
  • Yoo S; Office of eHealth Research and Business, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
  • Song W; Office of eHealth Research and Business, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
  • Kim S; Department of Health Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Seongnam-si, Republic of Korea.
  • Baek H; Office of eHealth Research and Business, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
  • Lee JS; Office of eHealth Research and Business, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
  • Yoon YS; Department of Surgery, G Sam Hospital, Gunpo, Republic of Korea.
  • Yoon S; Department of Surgery, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
  • Lee HY; Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Kim KI; Department of Clinical Pharmacology and Therapeutic, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea.
J Med Internet Res ; 25: e42259, 2023 11 13.
Article em En | MEDLINE | ID: mdl-37955965

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Delírio do Despertar Limite: Aged / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Delírio do Despertar Limite: Aged / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article