Coronary heart disease (CHD) is a type of heart disease where the arteries of the heart cannot deliver enough oxygen-rich blood to the heart and it is the leading cause of death in the United States. Coronary heart disease occurs when plaque builds up in the arteries. The plaque can also cause blood clots which are the most common cause of heart attacks. It would be beneficial for patients if they were able to receive a reliable prediction of CHD while only undergoing the fewest and least invasive procedures for diagnosis.
This classification project attempts to predict if someone has CHD based on measurements which do not include coronary angiography, which is considered the gold standard for diagnosing coronary artery disease. In particular I would like to investigate which of the 13 features are most predictive of CHD so patients will undergo only the most necessary tests.
Files:
- project_chd.ipynb: Jupyter notebook with project details and analysis
- processed_cleveland.csv: Data used in project
Video Overview Link: https://youtu.be/kaNHe7ZLjwo