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An IoMT-Enabled Smart Healthcare Model to Monitor Elderly People Using Machine Learning Technique.
Khan, Muhammad Farrukh; Ghazal, Taher M; Said, Raed A; Fatima, Areej; Abbas, Sagheer; Khan, M A; Issa, Ghassan F; Ahmad, Munir; Khan, Muhammad Adnan.
Afiliación
  • Khan MF; School of Computer Science, National College of Business Administration and Economics, Lahore 54000, Pakistan.
  • Ghazal TM; Lahore Institute of Science and Technology, Lahore 54792, Pakistan.
  • Said RA; Center for Cyber Security, Faculty of Information Science and Technology, University Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia.
  • Fatima A; School of Information Technology, Skyline University College, University City Sharjah, 1797 Sharjah, UAE.
  • Abbas S; Canadian University Dubai, Dubai, UAE.
  • Khan MA; Department of Computer Science, Lahore Garrison University, Lahore 54792, Pakistan.
  • Issa GF; School of Computer Science, National College of Business Administration and Economics, Lahore 54000, Pakistan.
  • Ahmad M; Riphah School of Computing & Innovation, Faculty of Computing, Riphah International University Lahore Campus, Lahore 54000, Pakistan.
  • Khan MA; School of Information Technology, Skyline University College, University City Sharjah, 1797 Sharjah, UAE.
Comput Intell Neurosci ; 2021: 2487759, 2021.
Article en En | MEDLINE | ID: mdl-34868288
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Aprendizaje Automático Tipo de estudio: Prognostic_studies Límite: Aged / Humans Idioma: En Revista: Comput Intell Neurosci Asunto de la revista: INFORMATICA MEDICA / NEUROLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Aprendizaje Automático Tipo de estudio: Prognostic_studies Límite: Aged / Humans Idioma: En Revista: Comput Intell Neurosci Asunto de la revista: INFORMATICA MEDICA / NEUROLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Estados Unidos