Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: De-identification of medical records using conditional random fields and
  long short-term memory networks   The CEGS N-GRID 2016 Shared Task 1 in Clinical Natural Language Processing
focuses on the de-identification of psychiatric evaluation records. This paper
describes two participating systems of our team, based on conditional random
fields (CRFs) and long short-term memory networks (LSTMs). A pre-processing
module was introduced for sentence detection and tokenization before
de-identification. For CRFs, manually extracted rich features were utilized to
train the model. For LSTMs, a character-level bi-directional LSTM network was
applied to represent tokens and classify tags for each token, following which a
decoding layer was stacked to decode the most probable protected health
information (PHI) terms. The LSTM-based system attained an i2b2 strict
micro-F_1 measure of 89.86%, which was higher than that of the CRF-based
system.

3
The categories of this paper are: physics
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
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The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
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The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph