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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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Detalles Bibliográficos
Autores principales: Divita, Guy, Coale, Kathleen, Maldonado, Jonathan Camacho, Silva, Rafael Jiménez, Rasch, Elizabeth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485548/
https://www.ncbi.nlm.nih.gov/pubmed/36148210
http://dx.doi.org/10.3389/fdgth.2022.914171
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author Divita, Guy
Coale, Kathleen
Maldonado, Jonathan Camacho
Silva, Rafael Jiménez
Rasch, Elizabeth
author_facet Divita, Guy
Coale, Kathleen
Maldonado, Jonathan Camacho
Silva, Rafael Jiménez
Rasch, Elizabeth
author_sort Divita, Guy
collection PubMed
description 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.
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spelling pubmed-94855482022-09-21 Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text Divita, Guy Coale, Kathleen Maldonado, Jonathan Camacho Silva, Rafael Jiménez Rasch, Elizabeth Front Digit Health Digital Health 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. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9485548/ /pubmed/36148210 http://dx.doi.org/10.3389/fdgth.2022.914171 Text en © https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Divita, Guy
Coale, Kathleen
Maldonado, Jonathan Camacho
Silva, Rafael Jiménez
Rasch, Elizabeth
Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text
title Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text
title_full Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text
title_fullStr Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text
title_full_unstemmed Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text
title_short Extracting body function information using rule-based methods: Highlighting structure and formatting challenges in clinical text
title_sort extracting body function information using rule-based methods: highlighting structure and formatting challenges in clinical text
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485548/
https://www.ncbi.nlm.nih.gov/pubmed/36148210
http://dx.doi.org/10.3389/fdgth.2022.914171
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