Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text

This paper describes the identification of body function (BF) mentions within the clinical text within a large, national, heterogeneous corpus to highlight structural challenges presented by the clinical text. BF in clinical documents provides information on dysfunction or impairments in the functio...

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Veröffentlicht in:Frontiers in digital health 2022-09, Vol.4, p.914171-914171
Hauptverfasser: Divita, Guy, Coale, Kathleen, Maldonado, Jonathan Camacho, Silva, Rafael Jiménez, Rasch, Elizabeth
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Sprache:eng
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Zusammenfassung:This paper describes the identification of body function (BF) mentions within the clinical text within a large, national, heterogeneous corpus to highlight structural challenges presented by the clinical text. BF in clinical documents provides information on dysfunction or impairments in the function or structure of organ systems or organs. BF mentions are embedded in highly formatted structures where the formats include implied scoping boundaries that confound existing natural language processing segmentation and document decomposition techniques. This paper describes follow-up work to adapt a rule-based system created using National Institutes of Health records to a larger, more challenging corpus of Social Security Administration data. Results of these systems provide a baseline for future work to improve document decomposition techniques.
ISSN:2673-253X
2673-253X
DOI:10.3389/fdgth.2022.914171