Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Use of 'off-the-shelf' information extraction algorithms in clinical
  informatics: a feasibility study of MetaMap annotation of Italian medical
  notes   Information extraction from narrative clinical notes is useful for patient
care, as well as for secondary use of medical data, for research or clinical
purposes. Many studies focused on information extraction from English clinical
texts, but less dealt with clinical notes in languages other than English. This
study tested the feasibility of using 'off the shelf' information extraction
algorithms to identify medical concepts from Italian clinical notes. We used
MetaMap to map medical concepts to the Unified Medical Language System (UMLS).
The study addressed two questions: (Q1) to understand if it would be possible
to properly map medical terms found in clinical notes and related to the
semantic group of 'Disorders' to the Italian UMLS resources; (Q2) to
investigate if it would be feasible to use MetaMap as it is to extract these
medical concepts from Italian clinical notes. Results in EXP1 showed that the
Italian UMLS Metathesaurus sources covered 91% of the medical terms of the
'Disorders' semantic group, as found in the studied dataset. Even if MetaMap
was built to analyze texts written in English, it worked properly also with
texts written in Italian. MetaMap identified correctly about half of the
concepts in the Italian clinical notes. Using MetaMap's annotation on Italian
clinical notes instead of a simple text search improved our results of about 15
percentage points. MetaMap showed recall, precision and F-measure of 0.53, 0.98
and 0.69, respectively. Most of the failures were due to the impossibility for
MetaMap to generate Italian meaningful variants. MetaMap's performance in
annotating automatically translated English clinical notes was in line with
findings in the literature, with similar recall (0.75), F-measure (0.83) and
even higher precision (0.95).

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The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
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The categories of this paper are: chem-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: nlin
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The categories of this paper are: supr-con
2
The categories of this paper are: math
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The categories of this paper are: atom-ph
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci