Disease prediction over big data from healthcare institutions

Abstract

In today's technology powered world, human health keeping has become weak, and due to long screen times, and minimal exercise, humans now are much more prone to diseases in daily life. Hypertension, obesity, stroke etc. have become common phenomenon for a large part of population. In between all this, it is very important to be able to identify / at least predict possible diseases as soon as possible so that human lives are saved. Also, in recent years, healthcare industry has moved on from purely traditional disease diagnosis methods to also using new technology like Internet Of Things (IoT), Machine learning (ML), and Artificial Intelligence(AI) etc. for effective disease diagnosis. ML is a recently developed technology which is trained using proven data (previous patient data) which, here, will be provided by hospitals, etc. And using that, we will attempt to create an ML model which would predict the possible diseases one may have based on his symptoms. ML will help the system to predict automatically without any human intervention as needed by traditional diagnosis systems. ML can be supervised / unsupervised. But we will be only trying to find a solution using supervised learning.