AIMC Topic: Sleep Latency

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Predictors of Sleep Latency From the Multiple Sleep Latency Test: A Random Forest Investigation in a Community Sample.

Journal of sleep research Apr 21, 2025
This study aimed to advance the understanding of factors that predict mean sleep latency (MSL) on the multiple sleep latency test (MSLT) by applying machine learning methodology on a high-dimensional dataset from a large community sample. A cross-sec...
Humans Machine Learning Female Aged Cross-Sectional Studies Male Middle Aged Longitudinal Studies Random Forest Circadian Rhythm Polysomnography Wisconsin Sleep Latency
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Association Between Sleep Quality and Deep Learning-Based Sleep Onset Latency Distribution Using an Electroencephalogram.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society May 9, 2024
To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However, sleep monitoring typically requires more than 7 hours, which can be inefficient in termxs of data size and analysis. Therefore, we proposed to develop a deep lea...
Humans Algorithms Female Aged Adult Male Middle Aged Deep Learning Sleep Quality Electroencephalography Sleep Polysomnography Sleep Latency
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Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning.

Scientific reports Jul 13, 2018
Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of p...
Humans Databases, Factual Female Young Adult Adult Male ROC Curve Data Interpretation, Statistical Models, Biological Supervised Machine Learning Datasets as Topic Stochastic Processes Rare Diseases Narcolepsy Polysomnography Sleep, REM Sleep Latency
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