Sex-Specific and Regional Analysis of Heart Disease Prediction Using Machine Learning Algorithms: Insights from the UCI Irvine Public Heart Disease Datasets (Cleveland and Long Beach)
Jonathan Asanjarani
City University of New York Graduate Center
DATA 79000: Capstone Project and Thesis
Advisor: Johanna Devaney
November 25th, 2024

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Software and Tools Used

1. Google Colab
   • Description: Cloud-based Python environment with GPU access for accelerated computation.
   • URL: https://colab.research.google.com
   • Accessed: November 2024
2. Python
   • Version: 3.8
   • Description: High-level programming language used for data analysis, modeling, and visualization.
   • URL: https://www.python.org
   • Accessed: November 2024
3. Scikit-learn
   • Version: 1.2.0
   • Description: Library for machine learning algorithms, preprocessing, and evaluation.
   • URL: https://scikit-learn.org/stable/
   • Accessed: November 2024
4. XGBoost
   • Version: 1.6.0
   • Description: Gradient boosting library optimized for supervised learning tasks.
   • URL: https://xgboost.ai
   • Accessed: November 2024
5. Pandas
   • Version: 1.4.3
   • Description: Data manipulation and analysis library for structured data.
   • URL: https://pandas.pydata.org
   • Accessed: November 2024
6. NumPy
   • Version: 1.23.0
   • Description: Library for numerical computations and array processing.
   • URL: https://numpy.org
   • Accessed: November 2024
7. Matplotlib
   • Version: 3.6.0
   • Description: Visualization library for static and interactive graphics.
   • URL: https://matplotlib.org
   • Accessed: November 2024
8. Seaborn
   • Version: 0.12.2
   • Description: Statistical data visualization library built on Matplotlib.
   • URL: https://seaborn.pydata.org
   • Accessed: November 2024
9. ASCVD Risk Calculator
   • Version: GitHub Repository
   • Description: Python implementation of the ASCVD Risk Calculator for cardiovascular risk prediction.
   • URL: https://github.com/brandones/ascvd/tree/master
   • Accessed: November 2024

Datasets

1. Cleveland Heart Disease Dataset
   • Source: UCI Machine Learning Repository
   • Description: Dataset used for binary classification of heart disease presence.
   • URL: https://archive.ics.uci.edu/ml/datasets/Heart+Disease
   • Accessed: November 2024
2. VA Long Beach Heart Disease Dataset
   • Source: UCI Machine Learning Repository
   • Description: Dataset used for regional generalization of machine learning models.
   • URL: https://archive.ics.uci.edu/ml/datasets/Heart+Disease
   • Accessed: November 2024

Guidelines and Methodological References

1. Mueller, Andreas C., & Guido, Sarah
   • Title: Introduction to Machine Learning with Python
   • Publisher: O’Reilly Media
   • Publication Date: 2016
   • URL: https://github.com/dlsucomet/MLResources/blob/master/books/[ML]%20Introduction%20to%20Machine%20Learning%20with%20Python%20(2017).pdf
2. Software Sustainability Institute
   • Title: How to Cite and Describe Software
   • URL: https://www.software.ac.uk/how-cite-and-describe-software
   • Accessed: November 2024

Additional Resources for Citing Software and Data

1. Digital Curation Centre
   • Title: How to Cite Datasets and Link to Publications
   • Authors: Ball, A., & Duke, M.
   • Publisher: Digital Curation Centre
   • Publication Date: 2011
   • URL: http://www.dcc.ac.uk/resources/how-guides/cite-datasets
   • Accessed: November 2024
2. DataCite
   • Title: Why Cite Data?
   • URL: https://www.datacite.org/
   • Accessed: November 2024