Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Physiological State Space Model for Clinical Forecasting   Clinical forecasting based on electronic medical records (EMR) can uncover
the temporal correlations between patients' conditions and outcomes from
sequences of longitudinal clinical measurements. In this work, we propose an
intervention-augmented deep state space generative model to capture the
interactions among clinical measurements and interventions by explicitly
modeling the dynamics of patients' latent states. Based on this model, we are
able to make a joint prediction of the trajectories of future observations and
interventions. Empirical evaluations show that our proposed model compares
favorably to several state-of-the-art methods on real EMR data.

13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat