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Identification of Cardiac Patients Based on the Medical Conditions Using Machine Learning Models

Krishna Kumar1, Narendra Kumar2, Aman Kumar3,4

  • 1Department of Hydro and Renewable Energy, Indian Institute of Technology, Roorkee 247667, India.

Computational Intelligence and Neuroscience
|August 1, 2022
PubMed

Insights

Mathematical models, including artificial neural networks (ANN), can effectively identify heart disease patients. The ANN model demonstrated superior accuracy compared to curve fitting, offering a non-invasive diagnostic tool for medical professionals.

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Data Science

Background:

  • Chronic diseases, particularly heart disease, pose a significant global health challenge.
  • Coronary Artery Disease (CAD) is the most prevalent form, leading to heart attacks.
  • Traditional risk factors include hypertension, high cholesterol, and smoking, but accurate risk estimation remains complex.

Purpose of the Study:

  • To develop mathematical models for identifying patients with heart disease.
  • To compare the efficacy of curve fitting and artificial neural network (ANN) models in cardiac patient identification.
  • To provide a non-invasive method for early detection of heart disease.

Main Methods:

  • Utilized a medical database of patients diagnosed with heart disease.
  • Applied curve fitting techniques to model patient data.
  • Employed artificial neural network (ANN) models for comparative analysis.
  • Evaluated model performance using metrics such as R-squared, MAE, and RMSE.

Main Results:

  • The curve fitting model achieved an R-squared value of 0.6337, MAE of 0.293, and RMSE of 0.3688.
  • The ANN-based model demonstrated higher accuracy with an R-squared value of 0.8491, MAE of 0.20, and RMSE of 0.267.
  • ANN provided superior mathematical modeling for identifying heart disease patients compared to curve fitting.

Conclusions:

  • Artificial neural networks offer a more accurate approach to modeling and identifying heart disease patients.
  • The developed ANN model can assist medical professionals in diagnosing heart conditions without invasive procedures like angiography.
  • This research highlights the potential of AI in improving cardiovascular diagnostics and patient management.

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