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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
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.
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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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