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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Bibliographic Details
Main Authors: Guy Divita (Author), Kathleen Coale (Author), Jonathan Camacho Maldonado (Author), Rafael Jiménez Silva (Author), Elizabeth Rasch (Author)
Format: Book
Published: Frontiers Media S.A., 2022-09-01T00:00:00Z.
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Summary: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.
Item Description:2673-253X
10.3389/fdgth.2022.914171