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Neural Computing and Applications

, Volume 31, Supplement 1, pp 93–102 | Cite as

A novel recommender system based on FFT with machine learning for predicting and identifying heart diseases

  • Subhashini NarayanEmail author
  • E. Sathiyamoorthy
S.I. : Machine Learning Applications for Self-Organized Wireless Networks

Abstract

Recently, using of the intelligent technologies in the field of clinical decision making is increased rapidly to improve the lifestyles of patients and to help for reducing the workload and cost concerned in their healthcare. Heart diseases are one of the primary causes of death. However, if the diseases are identified at the early stage, the rate of death can be decreased. Thus, the disease identification process has become a matter of concern. An efficient medical recommendation system has been proposed in this paper, namely Fourier transformation-based heart disease prediction system (FTHDPS) by using Fourier transformation and machine learning technique to predict the chronic heart diseases effectively. Here, the input sequences rely on the patient’s time series details or data, which are crumbled by Fourier transformation for extracting the frequency information. In FTHDPS, a bagging model is utilized for predicting the conditions of the patients in advance to produce the absolute recommendation. In FTHDPS, three classifiers are used, namely artificial neural network, Naive Bayes and support vector machine, and real-life time series chronic heart disease data are used to evaluate the proposed model. The experimental results demonstrate that FTHDPS is much efficient to provide a reliable and accurate recommendation to the heart patients.

Keywords

Intelligent system Naive Bayes classifier Neural network Support vector machine Rough sets Heart disease 

Notes

Compliance with ethical standards

Conflict of interest

There is no conflict of interest between the authors to publish this manuscript.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.School of Information Technology and EngineeringVIT UniversityVelloreIndia

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