Guided Discrete Diffusion for Electronic Health Record Generation

arXiv:2404.12314v1 Announce Type: new
Abstract: Electronic health records (EHRs) are a pivotal data source that enables numerous applications in computational medicine, e.g., disease progression prediction, clinical trial design, and health economics and outcomes research. Despite wide usability, their sensitive nature raises privacy and confidentially concerns, which limit potential use cases. To tackle these challenges, we explore the use of generative models to synthesize artificial, yet realistic EHRs. While diffusion-based methods have recently demonstrated state-of-the-art performance in generating other data modalities …

abstract applications arxiv cases clinical clinical trial computational concerns cs.lg data design diffusion disease economics electronic electronic health record electronic health records health medicine nature pivotal prediction privacy raises records research type usability use cases