A dynamic graph-based PU-learning approach for sequential recommendation in rare disease detection Guanhao Wei* [1] , Yunlong Wang [1] , Li Zhou [1]

https://www.academia.edu/3071-0286/2/2/10.20935/AcadAI8326 Introduction: Rare diseases affect over 300 million people globally; their low prevalence often leads to high misdiagnosis rates. While Electronic Health Record (EHR) data offers opportunities for early detection, existing predictive models struggle to capture the complex, time-sensitive sequence of patient journeys. https://www.academia.edu/journals/academia-ai-and-applications/articles?source=journal-top-nav