Machine Learning Models for Symptom Detection and Disease Prediction

In the current worlds there are lots of new disease will be arrived. To prevent those disease in the early stage that is the big task for all the doctors. in predict the disease there are several models are available for predict the disease in one category such heart disease, diabetes, etc... In our model we will predict various disease prediction. For predict the disease we use machine learning approach. In our model will be work based on the input of the user symptoms then predict the disease that is match to the disease. In our model we will use two machine learning algorithm was Cat Boost Classifier and LGBM Classifier Algorithms. For collect the inputs we provide the simple interface for to enter the symptoms. We will train our model by rich dataset that will have the multiple correlations among them. Our model will predict the disease with highest accuracy rate and provide some additional information about the disease. Our model aims to help the people to know about the disease in early stage and people will make decisions about those disease in advance.