Relationship Discovery for Drug Recommendation

arXiv:2404.12228v1 Announce Type: cross
Abstract: Medication recommendation systems are designed to deliver personalized drug suggestions that are closely aligned with individual patient needs. Previous studies have primarily concentrated on developing medication embeddings, achieving significant progress. Nonetheless, these approaches often fall short in accurately reflecting individual patient profiles, mainly due to challenges in distinguishing between various patient conditions and the inability to establish precise correlations between specific conditions and appropriate medications. In response to these issues, we introduce DisMed, a model …

abstract arxiv challenges cs.ai cs.lg discovery embeddings patient personalized profiles progress recommendation recommendation systems relationship studies suggestions systems type