Artificial intelligence is opening up unprecedented possibilities in predictive medicine, particularly in diabetes, where the ability to promptly identify the risk of complications can radically change the quality and outcome of treatment.

With our team of physicians, researchers, computer engineers, and epidemiologists, we have developed AI-based predictive computing models capable of estimating, with statistical robustness, the likelihood of developing significant complications in people with diabetes.

By analyzing large amounts of longitudinal clinical data collected over time using Metaclinic, our electronic medical record, our algorithms identify recurring patterns and produce personalized predictions based on each patient's specific characteristics.

The models currently in use allow us to estimate the risk of ocular, cardiovascular, cerebrovascular, peripheral vascular, nephropathic and diabetic neuropathic complications.

The goal is twofold: to anticipate clinical interventions and improve overall patient care, making care more proactive and personalized. In many centers, predictive medicine is beginning to become an integral part of digital care pathways.