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BASH-GN: A New Machine Learning–Derived Questionnaire for Screening Obstructive Sleep Apnea
BASH-GN is a machine learning-based questionnaire designed to classify the risk of obstructive sleep apnea (OSA) by considering various risk factor subtypes. Compared with other commonly used OSA screening tools, the BASH-GN questionnaire demonstrated superior performance, making it a more effective option for identifying at-risk individuals. This questionnaire...
Published: 9/23/2024
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Inventor(s): Ao Li, Jiayan Huo, Stuart Quan, Janet Roveda
Keywords(s):
Category(s): Technology Classifications > Software & Information Technology > Health IT, Technology Classifications > Life Sciences > Diagnostics, Technology Classifications > Healthcare Portfolios > Sleep Disorders
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Deep Learning Algorithm for Detection of Cortical Arousal During Sleep
This invention is an end-to-end deep learning algorithm to detect cortical arousals during sleep using a one-night single lead electrocardiogram (ECG) signal. It is used to accurately detect arousal in home sleep tests, by reducing the false negative rate. The model combines both convolutional neural networks (CNN) and recurrent neural networks (RNN).
Background:
Sleep...
Published: 10/8/2024
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Inventor(s): Ao Li, Siteng Chen, Stuart Quan, Linda Powers, Janet Roveda
Keywords(s):
Category(s): Technology Classifications > Healthcare Portfolios > Sleep Disorders, Technology Classifications > Software & Information Technology > Health IT
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Artificial Neural Network Based Sleep Disordered Breathing Screening
Early detection of sleep disorders. Artificial Neural Network Based Sleep Disordered Breathing Screening.
Published: 8/23/2024
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Inventor(s): Ao Li, Stuart Quan, Janet Roveda
Keywords(s):
Category(s): Technology Classifications > Software & Information Technology > Health IT, Technology Classifications > Software & Information Technology > Web & Internet, Technology Classifications > Software & Information Technology > Databases & Data Mining
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