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Natural language processing of radiology reports to detect complications of ischemic stroke

Abstract:
Background
Abstraction of critical data from unstructured radiologic reports using natural language processing (NLP) is a powerful tool to automate the detection of important clinical features and enhance research efforts. We present a set of NLP approaches to identify critical findings in patients with acute ischemic stroke from radiology reports of computed tomography (CT) and magnetic resonance imaging (MRI).
Methods
We trained machine learnin... Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s12028-022-01513-3

Authors


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Institution:
University of Oxford
Division:
SSD
Department:
Saïd Business School
Oxford college:
Exeter College
Role:
Author
ORCID:
0000-0003-3737-4826
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Name:
National Institutes of Health
Publisher:
Springer Nature
Journal:
Neurocritical Care More from this journal
Volume:
37
Issue:
Supplement issue 2
Pages:
291-302
Place of publication:
United States
Publication date:
2022-05-09
Acceptance date:
2022-04-05
DOI:
EISSN:
1556-0961
ISSN:
1541-6933
Pmid:
35534660
Language:
English
Keywords:
Pubs id:
1259968
Local pid:
pubs:1259968
Deposit date:
2022-11-13

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