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Heart Disease Prediction Using k-Nearest Neighbor Classifier Based on Handwritten Text

  • Seema Kedar
  • D. S. Bormane
  • Vaishnavi Nair
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 410)

Abstract

Heart diseases are the major cause of mortality in developed as well as developing countries. Early prediction of heart disease is required to reduce the number of deaths occurring due to it and by using handwriting analysis we can achieve this. Handwriting of an individual shows the presence of a heart disease even before physical symptoms appear. The proposed system predicts presence of heart disease based on handwriting analysis using k-Nearest Neighbor classifier. It extracts ten writing features namely right slant, left slant, vertical lines, horizontal lines, total length of vertical baselines, total number of left slant lines, total length of horizontal baselines, total number of right slant lines, pen pressure and size from a writing sample and using this information it predicts heart disease and risk factors for heart disease like low blood pressure, and diabetes. The proposed system provides 75 % accuracy.

Keywords

Heart disease Handwriting analysis Writing features k-NN 

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.JSPM’s Rajarshi Shahu College of EngineeringSavitribai Phule Pune UniversityPuneIndia

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