Global Journal of Engineering and Technology Research (GJETR)

A Comparative Study: Prediction of Heart Disease During Stress Testing Device Based on Machine Learning and Artificial Techniques

Azba, Faris S. H., AlSaif, Omar, Farhan, Mazin N.

23 January 2026 · Vol. 2, Issue 1, pp. 19-24

DOI: 10.65150/EP-gjetr/V2E1/2026-04

Abstract

The heart is the most important organ in the human body. Given the dynamic nature of cardiac function under stress, predicting heart failure during physical exertion is a major challenge in clinical practice. Machine learning (ML) provides a transformative approach for analyzing complex physiological and clinical data and achieving accurate and timely predictions. This study aims to review the findings of previous studies on the use of AI in heart disease diagnosis. Several machine learning algorithms, including random forests, support vector machines (SVMs), deep neural networks (DNNs), and others, were evaluated to determine their predictive performance. The results showed that deep neural networks outperformed other models, achieving 92% accuracy and 94% sensitivity. Their ability to adapt to generally nonlinear patterns also demonstrate the importance of some features over others, such as cholesterol levels, blood pressure, chest pain, and heart rate. The study concludes by highlighting the importance of AI in supporting and assisting medical professionals, particularly in the field of heart health, which can advance beyond diagnosis and prediction.

Keywords: Heart Failure Prediction, machine learning, DNN, SVM, Heart Stress.

Read the full text on Global Journal of Engineering and Technology Research →The full peer-reviewed article and PDF are hosted on the journal's site (the version of record).

Azba, Faris S. H., AlSaif, Omar, Farhan, & Mazin N. (2026). A Comparative Study: Prediction of Heart Disease During Stress Testing Device Based on Machine Learning and Artificial Techniques. Global Journal of Engineering and Technology Research, 2(1), 19-24. https://doi.org/10.65150/EP-gjetr/V2E1/2026-04

@article{Azba2026,
  title   = {A Comparative Study: Prediction of Heart Disease During Stress Testing Device Based on Machine Learning and Artificial Techniques},
  author  = {Azba and Faris S. H. and AlSaif and Omar and Farhan and Mazin N.},
  journal = {Global Journal of Engineering and Technology Research},
  year    = {2026},
  volume  = {2},
  number  = {1},
  pages   = {19-24},
  doi     = {10.65150/EP-gjetr/V2E1/2026-04},
  url     = {https://doi.org/10.65150/EP-gjetr/V2E1/2026-04}
}

← Back to all articles