Healthcare Prediction Analysis in Big Data Using Random Forest Classifier
Keywords:
Machine Learning, Big Data, HealthcareAbstract
Rapid growth of Big Data in healthcare and biomedical fields helps in accurate analysis of medical information. In addition, it serves benefits like prediction of disease in advance, patient healthcare services etc. Conversely, accuracy in analysis decreases as the quality of training set is insufficient. Furthermore, many regions demonstrate superior characteristics of some chronicle diseases, which may discourage the prediction of disease risk. Here, we modernize Random Forest algorithm for better prediction of a chronic disease. We demonstrate an enhanced model of prediction on real-time patient information gathered from UCI repository. Our work focuses on one of the most popular chronic disease that is heart disease. The accuracy of prediction in our work reaches almost 97%.
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