Results 61 to 70 of about 162,786 (309)
Aging and Cancer, EarlyView.This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel +4 more
wiley +1 more source
Circadian and homeostatic modulation of sleep spindles in the human electroencephalogram [PDF]
, 2004 Sleep spindles are transient EEG oscillations of about 12-16 Hz. Together with slow waves, they hallmark the human non-REM sleep EEG. Sleep spindles originate in the thalamus and are suggested to have a sleep protective function by reducing sensory ...
Knoblauch, Vera
core +1 more source
Relationship of Epileptic Seizures to Sleep Stage and Sleep Depth [PDF]
Sleep, 2002 Interictal epileptiform discharges (IEDs) are facilitated by NREM stages 3 and 4 sleep and as sleep is deepening. To determine whether sleep influences seizures in a similar way to IEDs, we examined seizure rates in various stages of sleep in epilepsy patients undergoing overnight video-EEG-polysomnography (VPSG).Cross-sectional study.Neurology ...
Daniela, Minecan +3 more
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi +2 more
wiley +1 more source
Cellular and neurochemical basis of sleep stages in the thalamocortical network
eLife, 2016 The link between the combined action of neuromodulators in the brain and global brain states remains a mystery. In this study, using biophysically realistic models of the thalamocortical network, we identified the critical intrinsic and synaptic ...
Giri P Krishnan +7 more
doaj +1 more source
Ssleepnet: a structured sleep network for sleep staging based on sleep apnea severity
Complex & Intelligent Systems, 2023 Sleep stage classification is essential in evaluating sleep quality. Sleep disorders disrupt the periodicity of sleep stages, especially the common obstructive sleep apnea (OSA).
Xingfeng Lv +3 more
doaj +1 more source
Utility of Sleep Stage Transitions in Assessing Sleep Continuity [PDF]
Sleep, 2010 Sleep continuity is commonly assessed with polysomnographic measures such as sleep efficiency, sleep stage percentages, and the arousal index. The aim of this study was to examine whether the transition rate between different sleep stages could be used as an index of sleep continuity to predict self-reported sleep quality independent of other commonly ...
Alison, Laffan +3 more
openaire +2 more sources
Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
wiley +1 more source
The role of sleep in the psychological functioning of adolescents [PDF]
, 2016 Adolescents’ sleep is related to psychological functioning. The present cumulative dissertation examined three main issues: First, whether parents’ sleep patterns are associated with their adolescent children’ sleep Patterns using objective assessment of
Kalak, Nadeem
core +1 more source
3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning [PDF]
, 2023 A novel multi-channel-based 3D convolutional neural network (3D-CNN) is proposed in this paper to classify sleep stages. Time domain features, frequency domain features, and time-frequency domain features are extracted from electroencephalography (EEG ...
Ji, Xiaopeng +5 more
core +1 more source