Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier

Abstract

Abstract Recently, the mobile health care (m-healthcare) applications with Internet of Things (IoT) are providing the various dimensionalities and the online services. These applications have provided a new platform to the millions of people for getting benefit over the health tips frequently for living a healthy life. After the introduction of IoT technology and the related devices which are used in medical field, strengthened the various features of these healthcare online applications. The huge volume of big data is generated by IoT devices in healthcare environment. Cloud computing technology is used to handle the large volume of data and also provide the ease of use. In this scenario, cloud based applications are playing major role in this fast world. These medical applications are also used the Cloud Computing technology for secured storage and accessibility. For availing better services to the people over the online healthcare applications, we propose a new Cloud and IoT based Mobile Health care application for monitoring and diagnosing the serious diseases. Here, a new framework is developed for the public. In this work, a new systematic approach is used for the diabetes diseases and the related medical data is generated by using the UCI Repository dataset and the medical sensors for predicting the people who has affected with diabetes severely. In addition, we propose a new classification algorithm called Fuzzy Rule based Neural Classifier for diagnosing the disease and the severity. The experiments have been conducted by the standard UCI Repository dataset and the real health records which are collected from various hospitals. The experimental results show that the performance of the proposed work which outperforms the existing systems for disease prediction.