PROBRAIN

In neurorehabilitation, as in other medical areas, predictive models are used to set realistic expectations and goals, and tailor resources and efforts for cost-effective interventions. This is particularly crucial in brain injury rehabilitation due to its high prevalence and significant life disruption. Understanding the recovery and reintegration possibilities into family and social work environments for these individuals is a key concern for patients, families, and professionals in neurorehabilitation. Until now, predictive models have been based on a biomedical concept prevalent since the early 20th century, focusing on global aspects of morbidity and mortality. These models, centered around disease-related variables, overlook other factors like recovery capability, which greatly influence therapeutic outcomes. Neurorehabilitation, unlike other medical disciplines, focuses not on the disease or mortality but on restoring functionality and participation, essential for the unique human identity of survivors. The PROBRAIN project aims to create predictive models using artificial intelligence that emphasize these aspects, enhancing the self-identity of individuals with brain injuries. This project will consider personal variables of each participant and use complex, multidisciplinary models not previously studied and state-of-the-art artificial intelligence techniques, including machine and deep learning algorithms.