The stratification of the risk of complications related to persistent COVID symptoms both physiological and psychological in a personalized way would optimize the cost-effectiveness model for the management of these patients. Similarly, the early detection of complications associated with persistent COVID in patients belonging to vulnerable groups would improve care times and, therefore, the patient's prognosis.
The primary objective of this study is to complement the SENSING-AI cohort with biometric and psychometric data prospectively gathered from patients diagnosed with long COVID in the last year to drive the generation of AI-based risk prediction and stratification models.
