Multimodal Disease Prediction using Machine Learning and Deep Learning Techniques

Abstract

Good health is man’s greatest possession but in today’s world people get a lot of diseases because of several reasons. The ability to predict diseases accurately is a critical aspect of healthcare. Machine learning techniques are increasingly being used to improve disease prediction. In this paper, we present a multi-disease prediction system that uses machine learning and deep learning algorithms to predict the likelihood of several common diseases. Even Though there are a lot of algorithms and techniques to predict a disease, there is no proper system to identify multiple diseases in a single system. Hence this paper focuses on the prediction of multiple diseases using machine learning and deep learning algorithms. Our aim is to build a model which efficiently predicts diseases such as kidney, heart and diabetes, malaria using machine learning and deep learning algorithms. This helps to make a better prediction of disease. For accurate prediction we are going to use stacking and ensembling models which help to increase the accuracy of the model. We are going to implement all these models in flask web application.