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Data mining to understand health status preceding traumatic brain injury
The use of precision medicine is poised to increase in complex injuries such as traumatic brain injury (TBI), whose multifaceted comorbidities and personal circumstances create significant challenges in the domains of surveillance, management, and environmental mapping. Population-wide health admini...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6447542/ https://www.ncbi.nlm.nih.gov/pubmed/30944376 http://dx.doi.org/10.1038/s41598-019-41916-5 |
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author | Mollayeva, Tatyana Sutton, Mitchell Chan, Vincy Colantonio, Angela Jana, Sayantee Escobar, Michael |
author_facet | Mollayeva, Tatyana Sutton, Mitchell Chan, Vincy Colantonio, Angela Jana, Sayantee Escobar, Michael |
author_sort | Mollayeva, Tatyana |
collection | PubMed |
description | The use of precision medicine is poised to increase in complex injuries such as traumatic brain injury (TBI), whose multifaceted comorbidities and personal circumstances create significant challenges in the domains of surveillance, management, and environmental mapping. Population-wide health administrative data remains a rather unexplored, but accessible data source for identifying clinical associations and environmental patterns that could lead to a better understanding of TBIs. However, the amount of data structured and coded by the International Classification of Disease poses a challenge to its successful interpretation. The emerging field of data mining can be instrumental in helping to meet the daunting challenges faced by the TBI community. The report outlines novel areas for data mining relevant to TBI, and offers insight into how the above approach can be applied to solve pressing healthcare problems. Future work should focus on confirmatory analyses, which subsequently can guide precision medicine and preventive frameworks. |
format | Online Article Text |
id | pubmed-6447542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64475422019-04-10 Data mining to understand health status preceding traumatic brain injury Mollayeva, Tatyana Sutton, Mitchell Chan, Vincy Colantonio, Angela Jana, Sayantee Escobar, Michael Sci Rep Article The use of precision medicine is poised to increase in complex injuries such as traumatic brain injury (TBI), whose multifaceted comorbidities and personal circumstances create significant challenges in the domains of surveillance, management, and environmental mapping. Population-wide health administrative data remains a rather unexplored, but accessible data source for identifying clinical associations and environmental patterns that could lead to a better understanding of TBIs. However, the amount of data structured and coded by the International Classification of Disease poses a challenge to its successful interpretation. The emerging field of data mining can be instrumental in helping to meet the daunting challenges faced by the TBI community. The report outlines novel areas for data mining relevant to TBI, and offers insight into how the above approach can be applied to solve pressing healthcare problems. Future work should focus on confirmatory analyses, which subsequently can guide precision medicine and preventive frameworks. Nature Publishing Group UK 2019-04-03 /pmc/articles/PMC6447542/ /pubmed/30944376 http://dx.doi.org/10.1038/s41598-019-41916-5 Text en © The Author(s) 2019 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/. |
spellingShingle | Article Mollayeva, Tatyana Sutton, Mitchell Chan, Vincy Colantonio, Angela Jana, Sayantee Escobar, Michael Data mining to understand health status preceding traumatic brain injury |
title | Data mining to understand health status preceding traumatic brain injury |
title_full | Data mining to understand health status preceding traumatic brain injury |
title_fullStr | Data mining to understand health status preceding traumatic brain injury |
title_full_unstemmed | Data mining to understand health status preceding traumatic brain injury |
title_short | Data mining to understand health status preceding traumatic brain injury |
title_sort | data mining to understand health status preceding traumatic brain injury |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6447542/ https://www.ncbi.nlm.nih.gov/pubmed/30944376 http://dx.doi.org/10.1038/s41598-019-41916-5 |
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