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Machine Learning Methods in Predicting Patients with Suspected Myocardial Infarction Based on Short-Time HRV Data.
Chumachenko, Dmytro; Butkevych, Mykola; Lode, Daniel; Frohme, Marcus; Schmailzl, Kurt J G; Nechyporenko, Alina.
Afiliação
  • Chumachenko D; Mathematical Modelling and Artificial Intelligence Department, National Aerospace University Kharkiv Aviation Institute, 61072 Kharkiv, Ukraine.
  • Butkevych M; Molecular Biotechnology and Functional Genomics Department, Technical University of Applied Sciences Wildau, 15745 Wildau, Germany.
  • Lode D; Mathematical Modelling and Artificial Intelligence Department, National Aerospace University Kharkiv Aviation Institute, 61072 Kharkiv, Ukraine.
  • Frohme M; Molecular Biotechnology and Functional Genomics Department, Technical University of Applied Sciences Wildau, 15745 Wildau, Germany.
  • Schmailzl KJG; Molecular Biotechnology and Functional Genomics Department, Technical University of Applied Sciences Wildau, 15745 Wildau, Germany.
  • Nechyporenko A; ccc. Center for Connected Health Care UG, 16818 Wustrau, Germany.
Sensors (Basel) ; 22(18)2022 Sep 17.
Article em En | MEDLINE | ID: mdl-36146381
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Infarto do Miocárdio Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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XML
PubMed Links
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Infarto do Miocárdio Idioma: En Ano de publicação: 2022 Tipo de documento: Article