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All Journal Bulletin of Electrical Engineering and Informatics
Kadry, Seifedine
Beirut Arab Univeristy
Electrical & Electronics Engineering

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Development of an IoT-based and cloud-based disease prediction and diagnosis system for healthcare using machine learning algorithms Abdali-Mohammadi, Fardin; Meqdad, Maytham N.; Kadry, Seifedine
Bulletin of Electrical Engineering and Informatics List of Accepted Papers (with minor revisions)
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2716

Abstract

Internet of Things (IoT) refers to the practice of designing and modelingobjects connected to the Internet through computer networks. In the past fewyears, IoT-based health care programs have provided multidimensionalfeatures and services in real time. These programs provide hospitalization formillions of people to receive regular health updates for a healthier life.Induction of IoT devices in the healthcare environment have revitalizedmultiple features of these applications. In this paper, a disease diagnosissystem is designed based on the Internet of Things. In this system, first, thepatient's courtesy signals are recorded by wearable sensors. These signals arethen transmitted to a server in the network environment. This article alsopresents a new Hybrid Decision Making approach for diagnosis. In thismethod, a feature set of patient signals is initially created. Then thesefeatures go unnoticed on the basis of a learning model. A diagnosis is thenperformed using a neural fuzzy model. In order to evaluate this system, aspecific diagnosis of a specific disease, such as a diagnosis of a patient'snormal and unnatural pulse, or the diagnosis of diabetic problems, will besimulated.
Co-Authors Abdali-Mohammadi, Fardin Meqdad, Maytham N.