Health data mining system: Voting system of analytical techniques to identify the factors that influence in the performance of aesthetic surgeries

Abstract

At the global level, cosmetic surgeries have become constant procedures that require, as an indispensable step, attendance at an appointment, but many of these appointments do not culminate with a surgical procedure. In order to identify the factors that influence the performance of aesthetic surgeries, this article proposes an analytical model based on a voting system of several techniques such as correlation analysis, principal component analysis, decision trees, logistic regression and association rules. The analytical model is validated with data from a surgical office in the city of Medellín. The results indicate that patients who undergo a cosmetic surgery are those who: 1) claim to desire a second surgery; 2) the first surgery desired is facial, breast augmentation, bichectomy, abdominoplasty, implant and gluteal augmentation; 3) the body mass index is normal; 4) they do not have cigarette habits; And 5) have no family history of diabetes.