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Heart Risk Prediction System Based on Supervised ANN

  • Ashima KalraEmail author
  • Richa Tomar
  • Udit Tomar
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)

Abstract

As well said “health is wealth”, good health is the key to human happiness. But nowadays due to bad eating habits, stressful life and unawareness among people, the number of cases of death due to heart diseases is increasing day by day. With the help of machine learning techniques, this hazard can be minimized up to some extent by helping healthcare professionals in the quick and efficient prediction of diseases. The motive of this study is to detect the risk of heart disease through a supervised learning network. The paper uses the back propagation approach of neural network. The data set here consists of 180 samples with four attributes adapted from UCI Machine Repository. We have set 70% data for training, 15% data for validation and 15% data for testing. The system gives a better accuracy as compared to the previous researches and with a good figure. It shows an accuracy of 91% for training part which is a good value for any data.

Keywords

Neural network Attributes Training Error back propagation 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Electronics and Communication EngineeringChandigarh Engineering CollegeMohaliIndia

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