Virtual Booth

Cardiac rehabilitation is essential in healthcare, contributing to improved outcomes for various cardiovascular interventions and conditions. Despite its recognized significance, challenges persist in achieving successful rehabilitation, prompting the need for new, innovative solutions. This project aims to use a personalized approach to cardiac rehabilitation through the development of a Buddy Recommendation System. The system can potentially create a supportive network where patients can exchange motivation, encouragement, and coping strategies. Three different clustering algorithms were compared, namely K-Means, Agglomerative clustering and DBSCAN. K-Means with PCA technique emerges as the top-performing model, with Silhouette Score=0.831, Calinski-Harabasz Score=383.970, Davies Bouldin Index=0.679.