COPER: Continuous Patient State Perceiver. (arXiv:2208.03196v1 [cs.LG])

In electronic health records (EHRs), irregular time-series (ITS) occur
naturally due to patient health dynamics, reflected by irregular hospital
visits, diseases/conditions and the necessity to measure different vitals signs
at each visit etc. ITS present challenges in training machine learning
algorithms which mostly are built on assumption of coherent fixed dimensional
feature space. In this paper, we propose a novel COntinuous patient state
PERceiver model, called COPER, to cope with ITS in EHRs. COPER uses Perceiver
model and the concept …

arxiv continuous lg patient perceiver state