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Deep learning for electronic health records: a comparative review of multiple deep neural architectures

Abstract:

Despite the recent developments in deep learning models, their applications in clinical decision-support systems have been very limited. Recent digitalisation of health records, however, has provided a great platform for the assessment of the usability of such techniques in healthcare. As a result, the field is starting to see a growing number of research papers that employ deep learning on electronic health records (EHR) for personalised prediction of risks and health trajectories. While thi...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jbi.2019.103337

Authors


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Name:
Oxford Biomedical Research Centre
Grant:
A93270
More from this funder
Name:
Economic and Social Research Council
Grant:
ES/P011055/1
Publisher:
Elsevier
Journal:
Journal of Biomedical Informatics More from this journal
Volume:
101
Article number:
103337
Publication date:
2020-01-06
Acceptance date:
2019-11-04
DOI:
ISSN:
0010-4809
Language:
English
Keywords:
Pubs id:
pubs:1070088
UUID:
uuid:face8d01-abfc-4564-98ce-4def739b02d9
Local pid:
pubs:1070088
Source identifiers:
1070088
Deposit date:
2019-11-05

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