Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction.

Lee, Woojoo; Lee, Joongyub; Woo, Seoung-Il; Choi, Seong Huan; Bae, Jang-Whan; Jung, Seungpil; Jeong, Myung Ho; Lee, Won Kyung

Lee, Woojoo; Lee, Joongyub; Woo, Seoung-Il; Choi, Seong Huan; Bae, Jang-Whan; Jung, Seungpil; Jeong, Myung Ho; Lee, Won Kyung.

Afiliação

Lee W; Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.
Lee J; Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
Woo SI; Department of Cardiology, School of Medicine, Inha University Hospital, Inha University, Incheon, Republic of Korea.
Choi SH; Department of Cardiology, School of Medicine, Inha University Hospital, Inha University, Incheon, Republic of Korea.
Bae JW; Division of Cardiology, Department of Internal Medicine, Chungbuk National University College of Medicine, Cheongju, Republic of Korea.
Jung S; Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.
Jeong MH; Chonnam National University Hospital, Gwangju, Republic of Korea.
Lee WK; Department of Prevention and Management, School of Medicine, Inha University Hospital, Inha University, 27 Inhang-Ro, Jung-Gu, Incheon, Republic of Korea. bluewhale65@inha.ac.kr.

Sci Rep ; 11(1): 12886, 2021 06 18.

Article em En | MEDLINE | ID: mdl-34145358

Assuntos

Aprendizado de Máquina; Modelos Teóricos; Infarto do Miocárdio sem Supradesnível do Segmento ST/mortalidade; Idoso; Área Sob a Curva; Mortalidade Hospitalar; Humanos; Pessoa de Meia-Idade; Infarto do Miocárdio sem Supradesnível do Segmento ST/diagnóstico; Curva ROC; Reprodutibilidade dos Testes; Medição de Risco; Fatores de Risco; Fatores de Tempo

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Infarto do Miocárdio sem Supradesnível do Segmento ST / Modelos Teóricos Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Humans / Middle aged Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article

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