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Automated Diagnosis...
Automated Diagnosis Coding with Combined Text Representations
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Berndorfer, Stefan (författare)
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- Henriksson, Aron (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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(creator_code:org_t)
- IOS Press, 2017
- 2017
- Engelska.
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Ingår i: Informatics for Health. - : IOS Press. - 9781614997528 - 9781614997535 ; , s. 201-205
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.3...
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Abstract
Ämnesord
Stäng
- Automated diagnosis coding can be provided efficiently by learning predictive models from historical data; however, discriminating between thousands of codes while allowing a variable number of codes to be assigned is extremely difficult. Here, we explore various text representations and classification models for assigning ICD-9 codes to discharge summaries in MIMIC-III. It is shown that the relative effectiveness of the investigated representations depends on the frequency of the diagnosis code under consideration and that the best performance is obtained by combining models built using different representations.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
Nyckelord
- Electronic health records
- diagnosis coding
- predictive modeling
- Computer and Systems Sciences
- data- och systemvetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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