ArticleJournal of the American Medical Informatics Association : JAMIA2018
The National Sleep Research Resource: towards a sleep data commons.
Article in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 325 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
325 citing papers in PubMed, 1 synthesis or guideline pooled it, 858 citations in OpenAlex.
- Deep learning for EEG-based sleep stage classification: a review.Medical & biological engineering & computing · 2026Pooled it
- Closed-loop modulation of sleep in children undergoing intracranial recordings.Cell reports. Medicine · 2026Trial
- Growth and sleep outcomes after adenotonsillectomy in pediatric mild sleep-disordered breathing.Scientific reports · 2025Trial
- Automated deep learning-based arousal detection agrees with ten expert scorers in unseen data.Sleep · 2026Article
- Including auxiliary cases to address missing data issues through multiple-group models.Behavior research methods · 2026Article
- The DYNAM-O Toolbox: Characterizing Individualized Neural Signatures in Sleep EEG.bioRxiv : the preprint server for biology · 2026Article
- Differential associations of arousals and respiratory events on oxygen desaturation and resaturation parameters in sleep.Sleep & breathing = Schlaf & Atmung · 2026Article
- Wearable Sleep-Stage Classification: A Systematic Analysis of Signal Modalities, Representations, and Multimodal Fusion.Sensors (Basel, Switzerland) · 2026Article
- Article
- A multifaceted approach for obstructive sleep apnea classification from ECG signal using deep learning.Npj biological timing and sleep · 2026Article
- Melatonin Use and Polysomnographic Sleep Architecture in Children.JAMA network open · 2026Article
- A foundation model for sleep-based risk stratification and clinical outcomes.Nature communications · 2026Article
- The Potential of Ensemble-Based Automated Sleep Staging on Single-Channel EEG Signal From a Wearable Device.Journal of sleep research · 2026Article
- Transformer-Based Multi-Channel K-Complex Detection Algorithm Tailored for Elderly Patients With Amnestic Mild Cognitive Impairment.Journal of sleep research · 2026Article
- Determinants of fractal motor activity regulation: insights from a large community-dwelling multi-ethnic population.Research square · 2026Article
- Cardiovascular Disease, Sleep-Disordered Breathing, and Artificial Intelligence: From Neutral Trials to Precision Sleep Cardiology.Reviews in cardiovascular medicine · 2026Review
- Sleep EEG foundation models reveal within-stage microstructure that improves health screening beyond traditional stages.Research square · 2026Article
- A Lightweight Temporal-Spatial Fusion Network for Neonatal Sleep Staging.Bioengineering (Basel, Switzerland) · 2026Article
- Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.bioRxiv : the preprint server for biology · 2026Article
- Optimising Sleep Stage Detection Using a Minimal Non-EEG Physiological Signal Set and Deep Learning.Journal of sleep research · 2026Article
265 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
Objective: The gold standard for diagnosing sleep disorders is polysomnography, which generates extensive data about biophysical changes occurring during sleep. We developed the National Sleep Research Resource (NSRR), a comprehensive system for sharing sleep data. The NSRR embodies elements of a data commons aimed at accelerating research to address critical questions about the impact of sleep disorders on important health outcomes. Approach: We used a metadata-guided approach, with a set of common sleep-specific terms enforcing uniform semantic interpretation of data elements across three main components: (1) annotated datasets; (2) user interfaces for accessing data; and (3) computational tools for the analysis of polysomnography recordings. We incorporated the process for managing dataset-specific data use agreements, evidence of Institutional Review Board review, and the corresponding access control in the NSRR web portal. The metadata-guided approach facilitates structural and semantic interoperability, ultimately leading to enhanced data reusability and scientific rigor. Results: The authors curated and deposited retrospective data from 10 large, NIH-funded sleep cohort studies, including several from the Trans-Omics for Precision Medicine (TOPMed) program, into the NSRR. The NSRR currently contains data on 26 808 subjects and 31 166 signal files in European Data Format. Launched in April 2014, over 3000 registered users have downloaded over 130 terabytes of data. Conclusions: The NSRR offers a use case and an example for creating a full-fledged data commons. It provides a single point of access to analysis-ready physiological signals from polysomnography obtained from multiple sources, and a wide variety of clinical data to facilitate sleep research.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.