Predicting heart failure onset in the general population using a novel data-mining artificial intelligence method.

Miyashita, Yohei; Hitsumoto, Tatsuro; Fukuda, Hiroki; Kim, Jiyoong; Washio, Takashi; Kitakaze, Masafumi

Miyashita, Yohei; Hitsumoto, Tatsuro; Fukuda, Hiroki; Kim, Jiyoong; Washio, Takashi; Kitakaze, Masafumi.

Afiliación

Miyashita Y; Department of Legal Medicine, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, Japan.
Hitsumoto T; Department of Clinical Research and Development, National Cerebral and Cardiovascular Center, 6-1 Kishibe-Shimmachi, Suita, Osaka, Japan.
Fukuda H; Department of Clinical Research and Development, National Cerebral and Cardiovascular Center, 6-1 Kishibe-Shimmachi, Suita, Osaka, Japan.
Kim J; Kim Cardiovascular Clinic, 3-6-8 Katsuyama, Tennoji-ku, Osaka, Japan.
Washio T; The Institute of Scientific and Industrial Research, Osaka University, 1-1 Yamadaoka, Suita, Osaka, Japan.
Kitakaze M; Hanwa Memorial Hospital, 3-5-8 Minamisumiyoshi, Sumiyoshi-ku, Osaka, 558-0041, Japan. kitakaze@zf6.so-net.ne.jp.

Sci Rep ; 13(1): 4352, 2023 03 16.

Article en En | MEDLINE | ID: mdl-36928666

Asunto(s)

Inteligencia Artificial; Insuficiencia Cardíaca; Humanos; Insuficiencia Cardíaca/diagnóstico; Insuficiencia Cardíaca/epidemiología; Minería de Datos; Factores de Riesgo

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Insuficiencia Cardíaca Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: Japón

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