ReviewInternational journal of environmental research and public health2019
SleepOMICS: How Big Data Can Revolutionize Sleep Science.
Review in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
18 citing papers in PubMed, 40 citations in OpenAlex.
- The future of the sleep field using large language models in mental health care.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- The Complex Interaction Between Sleep-Related Information, Misinformation, and Sleep Health: Call for Comprehensive Research on Sleep Infodemiology and Infoveillance.JMIR infodemiology · 2024Article
- Evaluating the effectiveness of artificial intelligence-based tools in detecting and understanding sleep health misinformation: Comparative analysis using Google Bard and OpenAI ChatGPT-4.Journal of sleep research · 2024Article
- Revolutionizing Sleep Health: The Emergence and Impact of Personalized Sleep Medicine.Journal of personalized medicine · 2024Review
- Assessing the Accuracy of Generative Conversational Artificial Intelligence in Debunking Sleep Health Myths: Mixed Methods Comparative Study With Expert Analysis.JMIR formative research · 2024Article
- Paediatric sleep diagnostics in the 21st century: the era of "sleep-omics"?European respiratory review : an official journal of the European Respiratory Society · 2024Review
- Exploring the Potential of Big Data Analytics in Urban Epidemiology Control: A Comprehensive Study Using CiteSpace.International journal of environmental research and public health · 2023Review
- Wireless electroencephalography (EEG) to monitor sleep among patients being withdrawn from opioids: Evidence of feasibility and utility.Experimental and clinical psychopharmacology · 2022Article
- Publicly Available Health Research Datasets: Opportunities and Responsibilities.Nature and science of sleep · 2022Article
- Planetary sleep medicine: Studying sleep at the individual, population, and planetary level.Frontiers in public health · 2022Review
- Automated Apnea-Hypopnea Index from Oximetry and Spectral Analysis of Cardiopulmonary Coupling.Annals of the American Thoracic Society · 2021Article
- U-Sleep: resilient high-frequency sleep staging.NPJ digital medicine · 2021Article
- Sleep health, diseases, and pain syndromes: findings from an electronic health record biobank.Sleep · 2021Article
- The COVID-19 pandemic: reflections for the field of sleep medicine.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2020Article
- How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic.International journal of environmental research and public health · 2020Review
- Assessment of Mandibular Movement Monitoring With Machine Learning Analysis for the Diagnosis of Obstructive Sleep Apnea.JAMA network open · 2020Article
- The future of sleep health: a data-driven revolution in sleep science and medicine.NPJ digital medicine · 2020Review
- Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring.BMJ open · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. "Real-life" behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level ("sleepOMICS"), thus paving the way for a targeted, "one-size-does-not-fit-all" management of sleep disorders ("precision sleep medicine").
Indexed as
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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.