Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning what to look in chest X-rays with a recurrent visual attention
  model   X-rays are commonly performed imaging tests that use small amounts of
radiation to produce pictures of the organs, tissues, and bones of the body.
X-rays of the chest are used to detect abnormalities or diseases of the
airways, blood vessels, bones, heart, and lungs. In this work we present a
stochastic attention-based model that is capable of learning what regions
within a chest X-ray scan should be visually explored in order to conclude that
the scan contains a specific radiological abnormality. The proposed model is a
recurrent neural network (RNN) that learns to sequentially sample the entire
X-ray and focus only on informative areas that are likely to contain the
relevant information. We report on experiments carried out with more than
$100,000$ X-rays containing enlarged hearts or medical devices. The model has
been trained using reinforcement learning methods to learn task-specific
policies.

21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg