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A reference set of curated biomedical data and metadata from clinical case reports
Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexi...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244181/ https://www.ncbi.nlm.nih.gov/pubmed/30457569 http://dx.doi.org/10.1038/sdata.2018.258 |
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author | Caufield, J. Harry Zhou, Yijiang Garlid, Anders O. Setty, Shaun P. Liem, David A. Cao, Quan Lee, Jessica M. Murali, Sanjana Spendlove, Sarah Wang, Wei Zhang, Li Sun, Yizhou Bui, Alex Hermjakob, Henning Watson, Karol E. Ping, Peipei |
author_facet | Caufield, J. Harry Zhou, Yijiang Garlid, Anders O. Setty, Shaun P. Liem, David A. Cao, Quan Lee, Jessica M. Murali, Sanjana Spendlove, Sarah Wang, Wei Zhang, Li Sun, Yizhou Bui, Alex Hermjakob, Henning Watson, Karol E. Ping, Peipei |
author_sort | Caufield, J. Harry |
collection | PubMed |
description | Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials. |
format | Online Article Text |
id | pubmed-6244181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62441812018-11-21 A reference set of curated biomedical data and metadata from clinical case reports Caufield, J. Harry Zhou, Yijiang Garlid, Anders O. Setty, Shaun P. Liem, David A. Cao, Quan Lee, Jessica M. Murali, Sanjana Spendlove, Sarah Wang, Wei Zhang, Li Sun, Yizhou Bui, Alex Hermjakob, Henning Watson, Karol E. Ping, Peipei Sci Data Data Descriptor Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials. Nature Publishing Group 2018-11-20 /pmc/articles/PMC6244181/ /pubmed/30457569 http://dx.doi.org/10.1038/sdata.2018.258 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Caufield, J. Harry Zhou, Yijiang Garlid, Anders O. Setty, Shaun P. Liem, David A. Cao, Quan Lee, Jessica M. Murali, Sanjana Spendlove, Sarah Wang, Wei Zhang, Li Sun, Yizhou Bui, Alex Hermjakob, Henning Watson, Karol E. Ping, Peipei A reference set of curated biomedical data and metadata from clinical case reports |
title | A reference set of curated biomedical data and metadata from clinical case reports |
title_full | A reference set of curated biomedical data and metadata from clinical case reports |
title_fullStr | A reference set of curated biomedical data and metadata from clinical case reports |
title_full_unstemmed | A reference set of curated biomedical data and metadata from clinical case reports |
title_short | A reference set of curated biomedical data and metadata from clinical case reports |
title_sort | reference set of curated biomedical data and metadata from clinical case reports |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244181/ https://www.ncbi.nlm.nih.gov/pubmed/30457569 http://dx.doi.org/10.1038/sdata.2018.258 |
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