Predictive Method for Diabetic Medical Records Data Analysis Using Machine Learning and Hadoop

  • T. Ajay Kumar, Dr. B. Sankara Babu

Abstract

Presently days from social insurance businesses huge volume of information is creating. It is important to gather, store and procedure this information to find information from it and use it to take huge choices. Diabetic Mellitus (DM) is from the Non Communicable Diseases (NCD), and loads of individuals are experiencing it. Presently days, for creating nations, for example, India, DM has become a major medical problem. The DM is one of the basic diseases which has long haul difficulties related with it and furthermore pursues with different medical issues. With the assistance of innovation, it is important to fabricate a framework that store and break down the diabetic information and predict potential dangers likewise. Predictive investigation is a strategy that incorporates different information mining systems, ML algorithms and measurements those utilization present and past informational collections to pick up understanding and predict future dangers. In this work “machine learning calculation in Hadoop MapReduce environment are executed for Pima Indian diabetes informational index to discover missing qualities in it and to find designs from it. This work will have the option to predict kinds of diabetes are far reaching, related future dangers and as per the hazard level of patient the sort of treatment can be given”.

Published
2020-01-23
How to Cite
Dr. B. Sankara Babu, T. A. K. (2020). Predictive Method for Diabetic Medical Records Data Analysis Using Machine Learning and Hadoop. International Journal of Advanced Science and Technology, 29(1), 970 - 978. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/3589
Section
Articles