Application of Machine Learning to Predict Diseases Based on Symptoms in Rural India

Living in a place away from hospitals and medical aid, it is often difficult for some people in rural India to diagnose a disease at an early state. Though hospitals in urban areas are using advanced technology for diagnosis and prognosis, disease prediction is one of the hypercritical tasks. Providing sophisticated and accurate algorithms and techniques to overcome this issue will be revolutionary. In this paper, we present a machine learning technique using Decision Tree Algorithm (DTL) to interconnect the symptoms and rearrange them and retrieve the most probable diagnosis. This technique allows the system to self-learn without using programming. This paper presents a system for diagnosis of common diseases by entering the symptoms into the system.