Web Based Disease Prediction and Forecasting with KNN and RNN using Internet of Medical Things

Abstract

Maintaining a healthy lifestyle has been a difficult task for all the busy workers and innovators. In this fast growing era, detection of disease at the right time can save millions of life. But proper monitoring after detection is difficult. Emerging infectious diseases pose a growing threat to the human population. To Overcome this, a web based application which predicts the disease and forecast the health condition of the user and help them to maintain a healthy lifestyle is developed. The application is divided into two parts. One is ML based disease prediction using KNN algorithm. In this module, most common diseases are predicted for the body parts like Skin, Eye, Ear, Nail and Teeth using the symptoms entered by the user. They can also find the risk level of the disease and treatment for that specified disease. Other one is Forecasting and report generation using RNN algorithm. This module contains classification and forecasting of user's health using the data fetched from the lot simulation. The parameters used here are Heart Beat, Temperature, Blood Pressure and Oxygen Level. The reports with graphical representation is implemented for the better understanding of the user. The web application also includes the doctor's suggestion who are specialists to that particular disease. As an added feature, health and food tips with precautions to be taken to control the disease are given to the user.