Machine Learning Base Sickle Disease Prediction and Recommendation System

Authors: Apeksha Bhujbal, Diksha Mali, Khushboo Singh

DOI: https://doi.org/10.17605/OSF.IO/WKET5

Short DOI: https://doi.org/ghqfg3

Country: India

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Abstract: 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.

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

Paper Id: 626

Published On: 2020-03-10

Published In: Volume 8, Issue 2, March-April 2020

Cite This: Machine Learning Base Sickle Disease Prediction and Recommendation System - Apeksha Bhujbal, Diksha Mali, Khushboo Singh - IJIRMPS Volume 8, Issue 2, March-April 2020. DOI 10.17605/OSF.IO/WKET5

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