• Shivani Pawar
• Yogita Sonawale
• Dipali Narkhede
• Prof. S. A. Sagar

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 patient’s 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.

Sickle Cell Disease; Machine Learning Algorithm; Mobile Healthcare Service; Real-time data; Self-care Management System; E-Health.

"Healthcare System for Sickle Cell Prediction and Management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.45-47, May-2020, Available :http://www.jetir.org/papers/JETIR2005309.pdf

"Healthcare System for Sickle Cell Prediction and Management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp45-47, May-2020, Available at : http://www.jetir.org/papers/JETIR2005309.pdf