Machine Learning Techniques and Insights for Cardiovascular or Heart Disease Prediction

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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Publication Details

Journal
Academic International Journal of Engineering Science
Published
2025-06-27
DOI
https://doi.org/10.59675/e313
Citations
1
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
2.94
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article

Machine Learning Techniques and Insights for Cardiovascular or Heart Disease Prediction

Mujiba Shaima, Estak Ahmed, Sharmin Sultana Akhi, Mazharul Islam Tusher et al.
1 citations
Academic International Journal of Engineering Science
Artificial Intelligence in Healthcare
2.94
article

Machine Learning Techniques and Insights for Cardiovascular or Heart Disease Prediction

Mujiba Shaima, Estak Ahmed, Sharmin Sultana Akhi, Mazharul Islam Tusher, Rayhan Hassan Mahin
article en
1 citations

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

Academic International Journal of Engineering ScienceVol. 3(01)
Monroe University (US), University of Louisiana at Monroe (US)
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare
2.94
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