Your browser doesn't support javascript.
loading
Flamingo-Optimization-Based Deep Convolutional Neural Network for IoT-Based Arrhythmia Classification.
Kumar, Ashwani; Kumar, Mohit; Mahapatra, Rajendra Prasad; Bhattacharya, Pronaya; Le, Thi-Thu-Huong; Verma, Sahil; Mohiuddin, Khalid.
Afiliação
  • Kumar A; Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, NCR Campus, Ghaziabad 201204, India.
  • Kumar M; MIT Art, Design and Technology University, Pune 412201, India.
  • Mahapatra RP; Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, NCR Campus, Ghaziabad 201204, India.
  • Bhattacharya P; Department of Computer Science and Engineering, Amity School of Engineering and Technology, Research and Innovation Cell, Amity University, Kolkata 700135, India.
  • Le TT; Blockchain Platform Research Center, Pusan National University, Busan 609735, Republic of Korea.
  • Verma S; Faculty of Computer Science and Engineering, Uttaranchal University University, Dehradun 248007, India.
  • Kavita; Blockchain Platform Research Center, Pusan National University, Busan 609735, Republic of Korea.
  • Mohiuddin K; Faculty of Information Systems, King Khalid University, Abha 62529, Saudi Arabia.
Sensors (Basel) ; 23(9)2023 Apr 28.
Article em En | MEDLINE | ID: mdl-37177564
Assuntos
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Arritmias Cardíacas / Redes Neurais de Computação Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Arritmias Cardíacas / Redes Neurais de Computação Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article