Machine Learning Techniques and Insights for Cardiovascular or Heart Disease Prediction

Authors

  • Mujiba Shaima Department of Computer Science, Monroe University, New York, USA. Author
  • Mazharul Islam Tusher Department of Computer Science, Monroe University, New York, USA. Author
  • Estak Ahmed Department of Computer Science, Monroe University, New York, USA Author
  • Sharmin Sultana Akhi Department of Computer Science, Monroe University, New York, USA Author
  • Rayhan Hassan Mahin Department of Computer Science, Monroe University, New York, USA Author

DOI:

https://doi.org/10.59675/E313

Keywords:

Heart Disease Prediction, Early Detection, Cardiovascular Health, Gradient Boosting Machines, K- Nearest Neighbors, Artificial Neural Networks.

Abstract

 Heart disease has been one of the major health concerns over the decades regardless of age, weight, or gender. Here in the article, we try to highlight the importance of early detection and the prevention of life-threatening heart-related diseases, including heart attacks and strokes. For this review paper, we include raw data from clinics and also include the famous Framingham Heart Study dataset, which is a popular cardiovascular dataset, including patient records that emphasize important human risk factors including age, blood pressure, cholesterol, smoking status, and family history. Precision, recall, accuracy, F1-score, and ROC-AUC metrics are such techniques and algorithms that are used to evaluate the implementation and performance of advanced machine learning approaches, including Gradient Boosting Machines (GBM), K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Convolutional Neural Network (CNN) and many more. Here, we

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Machine Learning Techniques and Insights for Cardiovascular or Heart Disease Prediction

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Published

2025-06-27

Issue

Vol. 3 No. 01 (2025)

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Articles

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Copyright (c) 2025 Academic International Journal of Engineering Sciences

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How to Cite

Mujiba Shaima, Mazharul Islam Tusher, Estak Ahmed, Sharmin Sultana Akhi, & Rayhan Hassan Mahin. (2025). Machine Learning Techniques and Insights for Cardiovascular or Heart Disease Prediction. Academic International Journal of Engineering Science, 3(01), 22-35. https://doi.org/10.59675/E313