An iomt-enabled smart healthcare model to monitor elderly people using machine learning technique

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dc.contributor.authorKhan, Muhammad Farrukh
dc.contributor.authorGhazal, Taher M.
dc.contributor.authorSaid, Raed A.
dc.contributor.authorFatima, Areej
dc.contributor.authorAbbas, Sagheer
dc.contributor.authorKhan, M.A.
dc.contributor.authorIssa, Ghassan F.
dc.contributor.authorAhmad, Munir
dc.contributor.authorKhan, Muhammad Adnan
dc.date.accessioned2021-12-28T10:23:05Z
dc.date.available2021-12-28T10:23:05Z
dc.date.copyright© 2021
dc.date.issued2021
dc.descriptionThis article is not available at CUD collection. The version of scholarly record of this article is published in Computational Intelligence and Neuroscience (2021), available online at: https://doi.org/10.1155/2021/2487759en_US
dc.description.abstractThe Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many factors, including the widespread and growing availability of wearables and the ever-decreasing cost of sensor-based technology. The cost of related healthcare will rise as the global population of elderly people grows in parallel with an overall life expectancy that demands affordable healthcare services, solutions, and developments. IoMT may bring revolution in the medical sciences in terms of the quality of healthcare of elderly people while entangled with machine learning (ML) algorithms. The effectiveness of the smart healthcare (SHC) model to monitor elderly people was observed by performing tests on IoMT datasets. For evaluation, the precision, recall, fscore, accuracy, and ROC values are computed. The authors also compare the results of the SHC model with different conventional popular ML techniques, e.g., support vector machine (SVM), K-nearest neighbor (KNN), and decision tree (DT), to analyze the effectiveness of the result. © 2021 Muhammad Farrukh Khan et al.en_US
dc.identifier.citationKhan, M. F., Ghazal, T. M., Said, R. A., Fatima, A., Abbas, S., Khan, M. A., . . . Khan, M. A. (2021). An iomt-enabled smart healthcare model to monitor elderly people using machine learning technique. Computational Intelligence and Neuroscience, 2021 https://doi.org/10.1155/2021/2487759en_US
dc.identifier.issn16875265
dc.identifier.urihttps://doi.org/10.1155/2021/2487759
dc.identifier.urihttp://hdl.handle.net/20.500.12519/482
dc.language.isoenen_US
dc.publisherHindawi Limiteden_US
dc.relationAuthors Affiliations : Khan, M.F., School of Computer Science, National College of Business Administration and Economics, Lahore, 54000, Pakistan, Lahore Institute of Science and Technology, Lahore, 54792, Pakistan; Ghazal, T.M., Center for Cyber Security, Faculty of Information Science and Technology, University Kebangsaan Malaysia (UKM) Bangi, Selangor, 43600, Malaysia, School of Information Technology, Skyline University College, University City Sharjah, Sharjah, 1797, United Arab Emirates; Said, R.A., Canadian University Dubai, Dubai, United Arab Emirates; Fatima, A., Department of Computer Science, Lahore Garrison University, Lahore, 54792, Pakistan; Abbas, S., School of Computer Science, National College of Business Administration and Economics, Lahore, 54000, Pakistan; Khan, M.A., Riphah School of Computing and Innovation, Faculty of Computing, Riphah International University Lahore Campus, Lahore, 54000, Pakistan; Issa, G.F., School of Information Technology, Skyline University College, University City Sharjah, Sharjah, 1797, United Arab Emirates; Ahmad, M., School of Computer Science, National College of Business Administration and Economics, Lahore, 54000, Pakistan; Khan, M.A., Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University13120, South Korea
dc.relation.ispartofseriesComputational Intelligence and Neuroscience;Volume 2021
dc.rightsCreative Commons Attribution License
dc.rights.holderCopyright : © 2021 Muhammad Farrukh Khan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectDecision treesen_US
dc.subjectHealth careen_US
dc.subjectNearest neighbor searchen_US
dc.subjectSupport vector machinesen_US
dc.subjectWearable technologyen_US
dc.subjectCloud platformsen_US
dc.subjectElderly peopleen_US
dc.subjectGlobal populationen_US
dc.subjectHealth care modelingen_US
dc.subjectHealth dataen_US
dc.subjectHealthcare servicesen_US
dc.subjectLife expectanciesen_US
dc.subjectMachine learning techniquesen_US
dc.subjectMedical scienceen_US
dc.subjectQuality of health careen_US
dc.titleAn iomt-enabled smart healthcare model to monitor elderly people using machine learning techniqueen_US
dc.typeArticleen_US

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