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A large collection of real-world pediatric sleep studies
Despite being crucial to health and quality of life, sleep—especially pediatric sleep—is not yet well understood. This is exacerbated by lack of access to sufficient pediatric sleep data with clinical annotation. In order to accelerate research on pediatric sleep and its connection to health, we cre...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296671/ https://www.ncbi.nlm.nih.gov/pubmed/35853958 http://dx.doi.org/10.1038/s41597-022-01545-6 |
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author | Lee, Harlin Li, Boyue DeForte, Shelly Splaingard, Mark L. Huang, Yungui Chi, Yuejie Linwood, Simon L. |
author_facet | Lee, Harlin Li, Boyue DeForte, Shelly Splaingard, Mark L. Huang, Yungui Chi, Yuejie Linwood, Simon L. |
author_sort | Lee, Harlin |
collection | PubMed |
description | Despite being crucial to health and quality of life, sleep—especially pediatric sleep—is not yet well understood. This is exacerbated by lack of access to sufficient pediatric sleep data with clinical annotation. In order to accelerate research on pediatric sleep and its connection to health, we create the Nationwide Children’s Hospital (NCH) Sleep DataBank and publish it at Physionet and the National Sleep Research Resource (NSRR), which is a large sleep data common with physiological data, clinical data, and tools for analyses. The NCH Sleep DataBank consists of 3,984 polysomnography studies and over 5.6 million clinical observations on 3,673 unique patients between 2017 and 2019 at NCH. The novelties of this dataset include: (1) large-scale sleep dataset suitable for discovering new insights via data mining, (2) explicit focus on pediatric patients, (3) gathered in a real-world clinical setting, and (4) the accompanying rich set of clinical data. The NCH Sleep DataBank is a valuable resource for advancing automatic sleep scoring and real-time sleep disorder prediction, among many other potential scientific discoveries. |
format | Online Article Text |
id | pubmed-9296671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92966712022-07-21 A large collection of real-world pediatric sleep studies Lee, Harlin Li, Boyue DeForte, Shelly Splaingard, Mark L. Huang, Yungui Chi, Yuejie Linwood, Simon L. Sci Data Data Descriptor Despite being crucial to health and quality of life, sleep—especially pediatric sleep—is not yet well understood. This is exacerbated by lack of access to sufficient pediatric sleep data with clinical annotation. In order to accelerate research on pediatric sleep and its connection to health, we create the Nationwide Children’s Hospital (NCH) Sleep DataBank and publish it at Physionet and the National Sleep Research Resource (NSRR), which is a large sleep data common with physiological data, clinical data, and tools for analyses. The NCH Sleep DataBank consists of 3,984 polysomnography studies and over 5.6 million clinical observations on 3,673 unique patients between 2017 and 2019 at NCH. The novelties of this dataset include: (1) large-scale sleep dataset suitable for discovering new insights via data mining, (2) explicit focus on pediatric patients, (3) gathered in a real-world clinical setting, and (4) the accompanying rich set of clinical data. The NCH Sleep DataBank is a valuable resource for advancing automatic sleep scoring and real-time sleep disorder prediction, among many other potential scientific discoveries. Nature Publishing Group UK 2022-07-19 /pmc/articles/PMC9296671/ /pubmed/35853958 http://dx.doi.org/10.1038/s41597-022-01545-6 Text en © The Author(s) 2022 https://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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Lee, Harlin Li, Boyue DeForte, Shelly Splaingard, Mark L. Huang, Yungui Chi, Yuejie Linwood, Simon L. A large collection of real-world pediatric sleep studies |
title | A large collection of real-world pediatric sleep studies |
title_full | A large collection of real-world pediatric sleep studies |
title_fullStr | A large collection of real-world pediatric sleep studies |
title_full_unstemmed | A large collection of real-world pediatric sleep studies |
title_short | A large collection of real-world pediatric sleep studies |
title_sort | large collection of real-world pediatric sleep studies |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296671/ https://www.ncbi.nlm.nih.gov/pubmed/35853958 http://dx.doi.org/10.1038/s41597-022-01545-6 |
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