The study aims to enhance clinical decision-making by analyzing key risk factors for intracranial aneurysms using biomarkers. It seeks to overcome traditional analysis limitations, which assume factor independence. A Bayesian network was developed from 1248 patient records to assess the likelihood of diagnosed ruptured versus unruptured aneurysms, based on phenotypic factors such as family history, sex, age at diagnosis, and aneurysm characteristics. Multicentric data validation is planned.