Doctormate- An Early Disease Prediction Approach using Multiple Machine Learning Algorithms

Abstract

Prediction of Multiple Diseases using Machine Learning Algorithms is a user-friendly ML model that is used to predict the disease based on the symptoms entered by the user and gives the best analysis of possible diseases. It is based on the symptoms collected from large datasets, which is taken from hospitals containing the textual discharge summaries of patient diseases. It is a model which gives tips to the user to maintain a healthy life and also it is used to find out possible diseases very earlier, the user is suffering from. Health industry plays a crucial role in curing patient’s diseases in today’s world. So our work is going to help the health industry in an indirect way where user does not need to go to hospital for checkup instead user get to know the accurate disease within few seconds by entering at least two symptoms. It can handle enormous amount of data. There are various procedures available for the treatment of various diseases across the world which may take more time for diagnosis and prediction. Machine learning is one of the most emerging technology which helps in prediction as well as diagnosis of a disease. This work is completely done by using Machine learning algorithms like Decision Tree Algorithm, Random Forest Algorithm, Naive Bayes Algorithm, K Nearest Neighbour algorithm where these algorithms are deployed on larger datasets, which is then preprocessed by using data mining techniques to achieve higher accuracy than the existing models.The lack of accuracy in existing models may lead to failure of diagnosis of the diseases in early stages and cause threat to patient’s life. This study has used Tkinter interface in Python programming language. The objective to attain higher accuracy improves the reliability of the model and gains patient’s trust for the cost-effective utilization of the proposed model.