Machine Learning Base Sickle Disease Prediction and Recommendation System

The expert systems and smart devices played a key role in the development of health care in terms of continuous monitoring of patients treatment and preservation of E-medication system. The basic challenge that patients faced is the fact of that is based on patient disease recommend the doctor. The problem is previously, machine learning techniques uses one classifier to classify data. This approach was not so reliable when it comes to disease prediction. To improve accuracy of prediction result, we have proposed ensemble method as collection of classifiers which will return prediction result which will have highest accuracy. Also, this system will manage a large amount of patients data and treatment preservation of E-medication system. In Healthcare System, the basic challenge that patients faces is the fact of difficulty in contacting physician specialists. System will provide communication way for treatment concerns