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Sleep apnea endotypes: from the physiological laboratory to scalable polysomnographic measures

Four key obstructive sleep apnea (OSA) endotypic traits have been identified, namely: collapsibility, upper airway muscle compensation, arousal threshold and loop gain. However, most methods for extracting these traits require specialized training and equipment not available in a standard sleep clinic, which has hampered the ability to assess the full impact of these traits on OSA outcomes. Keep reading

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By szhivotovsky on January 24, 2024 Jan 24, 2024 in Guest Blogger

Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction

Random forest machine learning is a popular predictive tool in medical research. However, when attempting to determine why the random forest model is predictive, applied researchers continue to rely on ‘out of bag’ (OOB) variable importance metrics (VIMPs) that are known to have considerable limitations within the statistics community, including a bias towards highly correlated features. Keep reading

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By szhivotovsky on January 18, 2024 Jan 18, 2024 in Guest Blogger

A prospective study of the association of weekend catch‑up sleep and sleep duration with mortality in middle‑aged adults

It remains to be determined whether and in which individuals weekend catch-up sleep (CUS) promotes health. The health effects of weekend CUS could differ depending on both the ability to obtain sufficient sleep during weekdays and amount of weekend CUS required to compensate for sleep lost during the week. We examined the longitudinal association of these two aspects of sleep with all-cause mortality. Keep reading

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By szhivotovsky on December 4, 2023 Dec 4, 2023 in Guest Blogger

U-Sleep’s resilience to AASM guidelines

AASM guidelines are the result of decades of efforts aimed at standardizing sleep scoring procedures, with the final goal of sharing a worldwide common methodology. The guidelines cover several aspects from the technical/digital specifications, e.g., recommended EEG derivations, to detailed sleep scoring rules according to age. Automated sleep scoring systems - e.g. highly performing deep learning (DL) algorithms - have always largely exploited the standards as fundamental guidelines. Keep reading

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By szhivotovsky on October 25, 2023 Oct 25, 2023 in Guest Blogger

An accessible and versatile deep learning-based sleep stage classifier

The Greifswald Sleep Stage Classifier (GSSC) is a highly accurate, deep learning-based automatic sleep stage classifier that priortises ease of use as well as accessibility for a broad range of potential applications and recording environments. Sleep staging can be performed within a simple GUI, the command-line, or integrated directly into the user's own Python code. Keep reading

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By szhivotovsky on October 17, 2023 Oct 17, 2023 in Guest Blogger

Longitudinal Trajectories of Spectral Power During Sleep in Middle-Aged and Older Adults

Textbook depictions of aging suggest a linear, almost deterministic, worsening of sleep architecture and sleep physiology in older adulthood. However, such conceptualizations of aging arise from group-averaged cross-sectional polysomnography data. What was the approach to solving the problem? We used a large-sample, longitudinal dataset to investigate individual trajectories in spectral power. Keep reading

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By szhivotovsky on October 5, 2023 Oct 5, 2023 in Guest Blogger

Deep learning for obstructive sleep apnea diagnosis based on single channel oximetry

Obstructive sleep apnea (OSA) affects more than 20% of the global adult population, with approximately 80% of cases remaining undiagnosed. Although home sleep test solutions have existed for almost two decades, they suffer from significant limitations. A recent review reported a misdiagnosis rate of 39% for home sleep tests. Keep reading

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By szhivotovsky on September 1, 2023 Sep 1, 2023 in Guest Blogger

Nighttime Sleep Duration and Variability in Children with Obstructive Sleep Apnea Syndrome: Sociodemographic Disparities and Neurobehavioral Outcomes

Due to adverse social and environmental factors, Black children and/or those living in lower socioeconomic status (SES) contexts are more likely to experience sleep disorders, including obstructive sleep apnea syndrome (OSAS), as well as short and irregular sleep duration. Children with OSAS also often have behavioral difficulties, but little is known about whether these challenges are worse when children also experience poor sleep, which is linked to similar child outcomes. Keep reading

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By szhivotovsky on August 10, 2023 Aug 10, 2023 in Guest Blogger

Can we still use existing sleep stage classification models in the label-scarce scenarios?

We aim to provide a realistic assessment of sleep stage classification (SSC) models in real-world label-scarce scenarios. Most of the proposed deep learning-based models assume access to a vast amount of labeled data, which is not usually achievable. What was the approach to solving the problem? We explored the efficacy of self-supervised learning (SSL) algorithms in scenarios with limited labeled data. Keep reading

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By szhivotovsky on July 17, 2023 Jul 17, 2023 in Guest Blogger

Check out Drs. Susan Redline and Shaun Purcell talk on "Open Science in Sleep Research: Tools and Resources, Promises and Challenges"

Dr. Susan Redline and Dr. Shaun Purcell give a talk for the “TUM Chronobiology and Health” series entitled “Open Science in Sleep Research: Tools and Resources, Promises and Challenges." Check it out here! Keep reading

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By szhivotovsky on June 12, 2023 Jun 12, 2023 in News