Personalization Based on Grouping Strategies for Short-Term Cardiovascular Event Risk Assessment.

Cardiovascular diseases are the main cause of death in Europe, representing 47% of all deaths. This could be avoided, if each patient underwent the most adequate treatment. For this to happen, it is important to determine the patient's risk of having a cardiovascular event. This is known as risk assessment, and can be done using risk scores. However, there are several risk scores with similar performances, which makes it difficult to choose the most adequate one. We propose to overcome this by combining risk scores using personalization based on groups, where new patients are assigned to the most similar group and consequently to the most adequate risk score. This eliminates the need to choose a specific tool, and improves the overall performance (when compared with the performance of individual tools). This strategy was validated using the Santa Cruz Dataset. The results obtained were able to maintain the highest sensitivity while improving the specificity in 13% when compared with the highest values achieved by the selected individual risk scores (GRACE, TIMI, PURSUIT).