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Machine learning-based model for predicting 1 year mortality of hospitalized patients with heart failure.
Tohyama, Takeshi; Ide, Tomomi; Ikeda, Masataka; Kaku, Hidetaka; Enzan, Nobuyuki; Matsushima, Shouji; Funakoshi, Kouta; Kishimoto, Junji; Todaka, Koji; Tsutsui, Hiroyuki.
Afiliación
  • Tohyama T; Center for Clinical and Translational Research of Kyushu University Hospital, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Ide T; Department of Cardiovascular Medicine, Faculty of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Ikeda M; Department of Cardiovascular Medicine, Faculty of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Kaku H; Department of Cardiovascular Medicine, Faculty of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Enzan N; Department of Cardiovascular Medicine, Faculty of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Matsushima S; Department of Cardiovascular Medicine, Faculty of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Funakoshi K; Department of Cardiovascular Medicine, Faculty of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Kishimoto J; Center for Clinical and Translational Research of Kyushu University Hospital, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Todaka K; Center for Clinical and Translational Research of Kyushu University Hospital, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
  • Tsutsui H; Center for Clinical and Translational Research of Kyushu University Hospital, Higashi-ku, Fukuoka-shi, Fukuoka, Japan.
ESC Heart Fail ; 8(5): 4077-4085, 2021 10.
Article en En | MEDLINE | ID: mdl-34390311
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Insuficiencia Cardíaca Tipo de estudio: Etiology_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: ESC Heart Fail Año: 2021 Tipo del documento: Article País de afiliación: Japón
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Insuficiencia Cardíaca Tipo de estudio: Etiology_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: ESC Heart Fail Año: 2021 Tipo del documento: Article País de afiliación: Japón