Assessing the Risk of Having Heart Attacks with Machine Learning

Authors

  • Chenlisha Sun Cate School, 1960 Cate Mesa Rd, Carpinteria, CA, the USA

DOI:

https://doi.org/10.54097/9vvdjj49

Keywords:

machine learning, logistic regression, heart attack prediction.

Abstract

Throughout the paper, what Machine Learning is and the Machine Learning technique known as Logistic Regression are explained. Afterward, this technique is used to analyze a set of data containing information about multiple patients. This information includes symptoms, as well as lab results such as cholesterol levels and whether the patient has a high chance of having a heart attack or not. The result of this analysis is a model that can be used on new patients to predict their risk of having a heart attack.

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References

[1] Burkov A. The hundred-page machine learning book. Vol. 1. Quebec City, QC, Canada: Andriy Burkov; 2019.

[2] Carbonell JG, Michalski RS, Mitchell TM. An overview of machine learning. Machine Learning. 1983;3-23.

[3] Raschka S, Mirjalili V. Python machine learning: Machine learning and deep learning with Python, scikit-learn, and TensorFlow 2. Packt Publishing Ltd; 2019.

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Published

23-12-2025

Issue

Vol. 159 (2025): 2nd International Conference on Mathematical Modeling, Algorithms and Data Processing (MMADP 2025)

Section

Articles

License

Copyright (c) 2025 Highlights in Science, Engineering and Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

Sun, C. (2025). Assessing the Risk of Having Heart Attacks with Machine Learning. Highlights in Science, Engineering and Technology, 159, 15-19. https://doi.org/10.54097/9vvdjj49