Healthcare Prediction Analysis in Big Data Using Random Forest Classifier

Authors(2) :-M. Arun Kumar, Dr. A. P. Siva Kumar

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%.

Authors and Affiliations

M. Arun Kumar
M.Tech, CSE Department, JNTUCEA, Ananthapuramu, Andhra Pradesh, India
Dr. A. P. Siva Kumar
Assistant Professor, CSE Department, JNTUCEA, Ananthapuramu, Andhra Pradesh, India

Machine Learning, Big Data, Healthcare

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Publication Details

Published in : Volume 3 | Issue 5 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 66-70
Manuscript Number : CSEIT183521
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

M. Arun Kumar, Dr. A. P. Siva Kumar, "Healthcare Prediction Analysis in Big Data Using Random Forest Classifier", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.66-70, May-June-2018.
Journal URL : http://ijsrcseit.com/CSEIT183521

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