Understanding Missingness in Time-series Electronic Health Records for Individualized Representation

arXiv:2402.15730v1 Announce Type: new
Abstract: With the widespread of machine learning models for healthcare applications, there is increased interest in building applications for personalized medicine. Despite the plethora of proposed research for personalized medicine, very few focus on representing missingness and learning from the missingness patterns in time-series Electronic Health Records (EHR) data. The lack of focus on missingness representation in an individualized way limits the full utilization of machine learning applications towards true personalization. In this brief communication, we …

abstract applications arxiv building cs.lg electronic electronic health records focus health healthcare machine machine learning machine learning models medicine patterns personalized records representation research series type understanding