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All Journal International Journal of Advances in Applied Sciences
Asadi Pushpa
Sree Vidyanikethan Engineering College
Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Disease prediction in big data healthcare using extended convolutional neural network techniques Asadi Srinivasulu; Asadi Pushpa
International Journal of Advances in Applied Sciences Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (676.343 KB) | DOI: 10.11591/ijaas.v9.i2.pp85-92

Abstract

Diabetes Mellitus is one of the growing fatal diseases all over the world. It leads to complications that include heart disease, stroke, and nerve disease, kidney damage. So, Medical Professionals want a reliable prediction system to diagnose Diabetes. To predict the diabetes at earlier stage, different machine learning techniques are useful for examining the data from different sources and valuable knowledge is synopsized. So, mining the diabetes data in an efficient way is a crucial concern. In this project, a medical dataset has been accomplished to predict the diabetes. The R-Studio and Pypark software was employed as a statistical computing tool for diagnosing diabetes.  The PIMA Indian database was acquired from UCI repository will be used for analysis. The dataset was studied and analyzed to build an effective model that predicts and diagnoses the diabetes disease earlier.
Co-Authors Asadi Srinivasulu