Symptom Based Health Prediction using Data Mining

The general day to day health of a person is vital for the efficient functioning of the human body. Taking certain prominent symptoms and their diseases to build a Machine learning model to predict common diseases based on real symptoms is the objective of this research. With the dataset of the most commonly exhibited diseases, we built a relation to predicting the possible disease based on the input of symptoms. The proposed model utilizes the capability of different Machine learning algorithms combined with text processing to achieve accurate prediction. Text processing has been implemented using Tokenization and, is combined with various algorithms to test the similarities and the outputs. In health industry, it provides several benefits such as pre-emptive detection of diseases, faster diagnosis, medical history for review of patients etc.