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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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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. |
format | Online Article Text |
id | pubmed-9485548 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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