Abstract
<jats:p>Drafting an Individual Rehabilitation Project requires precise goal-setting based on functional prognosis. However, patient stratification in rehabilitation is often hindered by the complexity of multimodal interventions. The PREPARE Rehab project, a four-year EU Horizon initiative, utilises Machine Learning and Artificial Intelligence (AI) to develop data-driven prediction tools across nine health conditions. This paper focuses on the children with idiopathic scoliosis cohort, utilising a dataset of over 21,000 patients. By standardising data through the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), the project aims to deliver a unified decision-support platform and AI-enhanced stratification models to prevent adult disability and optimise treatment intensity.</jats:p>