Familial hypercholesterolemia (FH) is a hereditary disease considered the main cause of premature coronary heart disease. The study, led by Dr. Alberto Zamora and featuring the participation of pre-doctoral researcher Miguel Camacho, has been published in the prestigious journal European Heart Journal – Digital Health.
The research analyzed data from 1,764 individuals with FH, sourced from the National Registry of the Spanish Atherosclerosis Society. Machine learning algorithms were used to combine clinical, genetic, and follow-up information to estimate the risk of severe cardiovascular events.
“"AI offers a more precise risk stratification than traditional models."
The algorithm allows for faster identification of high-risk patients, facilitating the adaptation of prevention and treatment strategies. Furthermore, the study is pioneering in incorporating a sex perspective, demonstrating that risk factors differ significantly between men and women, and applies explainable AI to understand its predictions.
