Heart disease is a leading cause of mortality worldwide, making it a significant public health concern. Understanding the factors associated with heart disease occurrence is crucial for prevention and intervention efforts. In our project, we aim to explore the predictors of heart disease using a dataset containing various patient attributes and heart disease diagnosis outcomes (Kreatsoulas, C., & Anand, S. S., 2010).
The central question guiding our analysis is: Can factors like cholosteral levels, and heart rate be used to predict if a patient has heart disease?