Title: Hybrid machine learning model for healthcare monitoring systems

Authors: M.K. Nallakaruppan; U. Senthil Kumaran

Addresses: School of Information Technology and Engineering, VIT University, Vellore, India ' School of Information Technology and Engineering, VIT University, Vellore, India

Abstract: The human life is facing a daunting task to handle the physical ailments. The late diagnosis of many diseases leads to serious complications on the human health. The lack of medical awareness is the primary cause of the lack of diagnosis and treatment which allows the disease grows easily. The prescribe work provides a solution to physically challenged or elderly people through web-based remote health monitoring facilities. The system collects the data, classifies them, apply the machine learning algorithms to ensure the data integrity. The reports are then generated and supplied to doctors for further examination of the patient record for taking medical decisions. We form a hybrid cluster of machine learning algorithms to ensure the increased accuracy and reduced error rate on the patient data measurement.

Keywords: support vector machine; SVM; body area network; BAN; internet of things; IoT; global system for mobile communication; GSM; wireless sensor networks; WSN; general packet radio services; GPRS.

DOI: 10.1504/IJITST.2020.10029361

International Journal of Internet Technology and Secured Transactions, 2020 Vol.10 No.5, pp.538 - 551

Received: 17 Sep 2018
Accepted: 16 Oct 2018
Published online: 15 Sep 2020 *

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