Comparative Analysis on Machine Learning and Deep Learning to Predict Post-Induction Hypotension.

Lee, Jihyun; Woo, Jiyoung; Kang, Ah Reum; Jeong, Young-Seob; Jung, Woohyun; Lee, Misoon; Kim, Sang Hyun

Lee, Jihyun; Woo, Jiyoung; Kang, Ah Reum; Jeong, Young-Seob; Jung, Woohyun; Lee, Misoon; Kim, Sang Hyun.

Afiliación

Lee J; SCH Media Labs, Soonchunhyang University, Asan 31538, Korea.
Woo J; SCH Media Labs, Soonchunhyang University, Asan 31538, Korea.
Kang AR; SCH Media Labs, Soonchunhyang University, Asan 31538, Korea.
Jeong YS; SCH Media Labs, Soonchunhyang University, Asan 31538, Korea.
Jung W; Department of Anesthesiology and Pain Medicine, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon 14584, Korea.
Lee M; Department of Anesthesiology and Pain Medicine, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon 14584, Korea.
Kim SH; Department of Anesthesiology and Pain Medicine, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon 14584, Korea.

Sensors (Basel) ; 20(16)2020 Aug 14.

Article en En | MEDLINE | ID: mdl-32824073

Asunto(s)

Aprendizaje Profundo; Hipotensión; Intubación Intratraqueal/efectos adversos; Aprendizaje Automático; Adulto; Anciano; Algoritmos; Femenino; Humanos; Hipotensión/diagnóstico; Masculino; Persona de Mediana Edad; Redes Neurales de la Computación

Palabras clave

anesthesia; biomedical sensor; deep learning; hypotension prediction; machine learning; vital records

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Automático / Aprendizaje Profundo / Hipotensión / Intubación Intratraqueal Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Sensors (Basel) Año: 2020 Tipo del documento: Article Pais de publicación: Suiza

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