Cross Language Application for Disease Prediction

Journal: GRENZE International Journal of Engineering and Technology
Authors: Shivani Butala, Advait Lad, Niket Parekh, Kiran Gawande
Volume: 6 Issue: 2
Grenze ID: 01.GIJET.6.2.10 Pages: 114-122

Abstract

The infrequent and inadequate medical facilities for the people residing in the remote villages of India due to the lack of medical experts is a glaring medical issue facing the country. The proposed cross language application aims to solve the aforementioned problem with the use of technology by utilizing Translation techniques and Machine Learning models. With the usage of the proposed application, the users can vocally input their experienced symptoms into the application in their local language and get as output, the disease they possibly might be suffering from within seconds. To increase the accuracy of the results, an ensemble approach is followed in the paper which is a combination of five Machine Learning Models and a majority decision technique is applied to get the most accurate results. The proposed application is able to predict the disease with an accuracy of 90% in return of the symptoms provided by the user.

Download Now << BACK

GIJET