A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform.

Elbagoury, Bassant M; Vladareanu, Luige; Vladareanu, Victor; Salem, Abdel Badeeh; Travediu, Ana-Maria; Roushdy, Mohamed Ismail

Elbagoury, Bassant M; Vladareanu, Luige; Vladareanu, Victor; Salem, Abdel Badeeh; Travediu, Ana-Maria; Roushdy, Mohamed Ismail.

Afiliação

Elbagoury BM; Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt.
Vladareanu L; Institute of Solid Mechanics of the Romanian Academy, 010141 Bucharest, Romania.
Vladareanu V; Institute of Solid Mechanics of the Romanian Academy, 010141 Bucharest, Romania.
Salem AB; Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt.
Travediu AM; Institute of Solid Mechanics of the Romanian Academy, 010141 Bucharest, Romania.
Roushdy MI; Faculty of Computers and Information Technology, Future University in Egypt, New Cairo 11835, Egypt.

Sensors (Basel) ; 23(7)2023 Mar 27.

Article em En | MEDLINE | ID: mdl-37050561

Assuntos

Aprendizado Profundo; Acidente Vascular Cerebral; Humanos; Inteligência Artificial; Retroalimentação; Acidente Vascular Cerebral/diagnóstico; Hospitais

Palavras-chave

Deep LSTM; GMDH neural networks; artificial intelligence; biomedical EMG signal processing; iomt-stacked convolutional neural networks; mobile health; stroke monitoring

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Acidente Vascular Cerebral / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Egito País de publicação: Suíça

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