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Found 8 papers, 1 papers with code
Annotation of Sleep Depth Index with Scalable Deep Learning Yields Novel Digital Biomarkers for Sleep Health
Traditional sleep staging categorizes sleep and wakefulness into five coarse-grained classes, overlooking subtle variations within each stage.
What Radio Waves Tell Us about Sleep
The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful.
Effects of Epileptiform Activity on Discharge Outcome in Critically Ill Patients
Having a maximum EA burden greater than 75% when untreated had a 22% increased chance of a poor outcome (severe disability or death), and mild but long-lasting EA increased the risk of a poor outcome by 14%.
Sleep Apnea and Respiratory Anomaly Detection from a Wearable Band and Oxygen Saturation
The objective is to automatically detect abnormal respiration and estimate the Apnea-Hypopnea-Index (AHI) with a wearable respiratory device, compared to an SpO2 signal or polysomnography using a large (n = 412) dataset serving as ground truth.
Automated Respiratory Event Detection Using Deep Neural Networks
Using 9, 656 polysomnography recordings from the Massachusetts General Hospital (MGH), we trained a neural network (WaveNet) based on a single respiratory effort belt to detect obstructive apnea, central apnea, hypopnea and respiratory-effort related arousals.
Natural Language Processing to Detect Cognitive Concerns in Electronic Health Records Using Deep Learning
Dementia is under-recognized in the community, under-diagnosed by healthcare professionals, and under-coded in claims data.
HAMLET: Interpretable Human And Machine co-LEarning Technique
Although cEEG monitoring yields large volumes of data, labeling costs and difficulty make it hard to build a classifier.
SLEEPNET: Automated Sleep Staging System via Deep Learning
Sleep disorders, such as sleep apnea, parasomnias, and hypersomnia, affect 50-70 million adults in the United States (Hillman et al., 2006).
