Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Improving Prediction of Low-Prior Clinical Events with Simultaneous
  General Patient-State Representation Learning   Low-prior targets are common among many important clinical events, which
introduces the challenge of having enough data to support learning of their
predictive models. Many prior works have addressed this problem by first
building a general patient-state representation model, and then adapting it to
a new low-prior prediction target. In this schema, there is potential for the
predictive performance to be hindered by the misalignment between the general
patient-state model and the target task. To overcome this challenge, we propose
a new method that simultaneously optimizes a shared model through multi-task
learning of both the low-prior supervised target and general purpose
patient-state representation (GPSR). More specifically, our method improves
prediction performance of a low-prior task by jointly optimizing a shared model
that combines the loss of the target event and a broad range of generic
clinical events. We study the approach in the context of Recurrent Neural
Networks (RNNs). Through extensive experiments on multiple clinical event
targets using MIMIC-III data, we show that the inclusion of general
patient-state representation tasks during model training improves the
prediction of individual low-prior targets.

20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
34
The categories of this paper are: chem-ph