How do we group patients based on their health risks? In this analysis, we apply K-Means Clustering to real patient data, using Age, BMI, LDL cholesterol, and Blood Pressure to identify distinct subgroups.
Using the Elbow Method, we determine the optimal number of clusters and summarize the results in a clear, data-driven way. This approach can help identify vital information in patient health, leading to more targeted interventions.