A multidisciplinary team of Italian experts has developed an algorithm that can predict the risk of falls and motor fluctuations (so-called "on - off" moments) typical of Parkinson's disease. Coordinated by the Azienda Provinciale per i Servizi Sanitari di Trento (APSS), the project involved the collaboration of the Fondazione Bruno Kessler (FBK), IRCCS Policlinico San Martino Hospital, and the University of Genoa. Parkinson's disease is the second most frequent neurodegenerative disease worldwide after Alzheimer's; cases are estimated to double by 2030 due to the increasing aging of the general population. Starting with the digitization, harmonization and organization of data from Parkinson's disease patients admitted to the clinical centers involved, the researchers structured disease-specific standardized datasets and identified patterns of clinical and neuropsychological variables, based on artificial intelligence, that are critical for predicting possible trajectories of the disease.