A major barrier to progress is the lack of standardized definitions for primary joint lesions and consistent grading of disease severity. Without harmonized criteria, clinical and research communities face difficulties in aligning diagnostic protocols and implementing personalized care strategies. This fragmentation not only limits data comparability across studies but also hinders the development of effective, patient-centered treatment plans. 

Our project addresses a critical need in hemophilia care by fostering global collaboration to define, standardise, diagnose, and manage joint bleeding more accurately and consistently. Leveraging expertise across medicine, computer science, and economics, we are developing an AI- and telemedicine-based prototype that combines advanced ultrasonography with intelligent image acquisition and analysis. Through accessible tools that enable both clinicians and patients to capture and interpret high-quality joint ultrasound images, our unified framework supports earlier and more reliable detection of hemarthrosis. By empowering clinicians, patients, and researchers with standardized, data-driven insights, we aim to reduce joint complications, preserve long-term joint health, and improve outcomes for people with hemophilia.