OntoMedRec: Logically-Pretrained Model-Agnostic Ontology Encoders for Medication Recommendation

arXiv:2401.15814v2 Announce Type: replace
Abstract: Most existing medication recommendation models learn representations for medical concepts based on electronic health records (EHRs) and make recommendations with learnt representations. However, most medications appear in the dataset for limited times, resulting in insufficient learning of their representations. Medical ontologies are the hierarchical classification systems for medical terms where similar terms are in the same class on a certain level. In this paper, we propose OntoMedRec, the logically-pretrained and model-agnostic medical Ontology Encoders for …

arxiv cs.lg model-agnostic ontology recommendation type