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

dc.contributor.author Khan, Muhammad Farrukh
dc.contributor.author Ghazal, Taher M.
dc.contributor.author Said, Raed A.
dc.contributor.author Fatima, Areej
dc.contributor.author Abbas, Sagheer
dc.contributor.author Khan, M.A.
dc.contributor.author Issa, Ghassan F.
dc.contributor.author Ahmad, Munir
dc.contributor.author Khan, Muhammad Adnan
dc.date.accessioned 2021-12-28T10:23:05Z
dc.date.available 2021-12-28T10:23:05Z
dc.date.copyright © 2021
dc.date.issued 2021
dc.description This 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/10.1155/2021/2487759 en_US
dc.description.abstract The 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.citation Khan, 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/10.1155/2021/2487759 en_US
dc.identifier.issn 16875265
dc.identifier.uri https://doi.org/10.1155/2021/2487759
dc.identifier.uri http://hdl.handle.net/20.500.12519/482
dc.language.iso en en_US
dc.publisher Hindawi Limited en_US
dc.relation Authors 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.ispartofseries Computational Intelligence and Neuroscience;Volume 2021
dc.rights Creative Commons Attribution License
dc.rights.holder Copyright : © 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.uri http://creativecommons.org/licenses/by/4.0/
dc.subject Decision trees en_US
dc.subject Health care en_US
dc.subject Nearest neighbor search en_US
dc.subject Support vector machines en_US
dc.subject Wearable technology en_US
dc.subject Cloud platforms en_US
dc.subject Elderly people en_US
dc.subject Global population en_US
dc.subject Health care modeling en_US
dc.subject Health data en_US
dc.subject Healthcare services en_US
dc.subject Life expectancies en_US
dc.subject Machine learning techniques en_US
dc.subject Medical science en_US
dc.subject Quality of health care en_US
dc.title An iomt-enabled smart healthcare model to monitor elderly people using machine learning technique en_US
dc.type Article en_US
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