An efficient and accurate distributed learning algorithm for modeling multi-site zero-inflated count outcomes
An efficient and accurate distributed learning algorithm for modeling multi-site zero-inflated count outcomes
Abstract Clinical research networks (CRNs), made up of multiple healthcare systems each with patient data from several care sites, are beneficial for studying rare outcomes and increasing generalizability of results. While CRNs encourage sharing aggregate data across healthcare systems, individual systems within CRNs often cannot share patient-level data due to …