AIMC Topic: Sleep Apnea Syndromes

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Machine Learning-based Sleep Staging in Patients with Sleep Apnea Using a Single Mandibular Movement Signal.

American journal of respiratory and critical care medicine Nov 15, 2021
Adult Sensitivity and Specificity Male Algorithms Humans Prospective Studies Machine Learning Female Pattern Recognition, Automated Middle Aged Polysomnography Mandible Sleep Stages Sleep Apnea Syndromes
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SomnNET: An SpO2 Based Deep Learning Network for Sleep Apnea Detection in Smartwatches.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
The abnormal pause or rate reduction in breathing is known as the sleep-apnea hypopnea syndrome and affects the quality of sleep of an individual. A novel method for the detection of sleep apnea events (pause in breathing) from peripheral oxygen satu...
Deep Learning Sleep Apnea Syndromes Humans Oxygen Saturation Sleep Apnea, Obstructive Neural Networks, Computer
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[Sleep apnea automatic detection method based on convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2021
Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution...
Humans Neural Networks, Computer Sleep Apnea Syndromes Machine Learning Sensitivity and Specificity Electrocardiography
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Deep learning enables sleep staging from photoplethysmogram for patients with suspected sleep apnea.

Sleep Nov 12, 2020
STUDY OBJECTIVES: Accurate identification of sleep stages is essential in the diagnosis of sleep disorders (e.g. obstructive sleep apnea [OSA]) but relies on labor-intensive electroencephalogram (EEG)-based manual scoring. Furthermore, long-term asse...
Humans Reproducibility of Results Deep Learning Sleep Stages Photoplethysmography Sleep Apnea Syndromes Sleep
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[VOTE versus ACLTE: comparison of two snoring noise classifications using machine learning methods].

HNO Sep 1, 2019
BACKGROUND: Acoustic snoring sound analysis is a noninvasive method for diagnosis of the mechanical mechanisms causing snoring that can be performed during natural sleep. The objective of this work is development and evaluation of classification sche...
Sleep Apnea Syndromes Sound Spectrography Snoring Humans Machine Learning Noise
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Tracheal Sound Analysis Using a Deep Neural Network to Detect Sleep Apnea.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Aug 15, 2019
STUDY OBJECTIVES: Portable devices for home sleep apnea testing are often limited by their inability to discriminate sleep/wake status, possibly resulting in underestimations. Tracheal sound (TS), which can be visualized as a spectrogram, carries inf...
Polysomnography Trachea Respiratory Sounds Middle Aged Deep Learning Sleep Apnea Syndromes Sensitivity and Specificity Male Humans Neural Networks, Computer Female Reproducibility of Results
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Convolutional Neural Networks to Detect Pediatric Apnea-Hypopnea Events from Oximetry.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Pediatric sleep apnea-hypopnea syndrome (SAHS) is a highly prevalent breathing disorder that is related to many negative consequences for the children's health and quality of life when it remains untreated. The gold standard for pediatric SAHS diagno...
Sleep Apnea Syndromes Polysomnography Oximetry Neural Networks, Computer Humans Quality of Life Child
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Sleep Apnea Severity Estimation from Respiratory Related Movements Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Sleep apnea is a common chronic respiratory disorder which occurs due to the repetitive complete or partial cessations of breathing during sleep. The gold standard assessment of sleep apnea requires full night polysomnography in a sleep laboratory wh...
Humans Female Aged Respiration Polysomnography Deep Learning Sleep Apnea Syndromes Sleep Adult Male Middle Aged
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Expert-level sleep scoring with deep neural networks.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2018
OBJECTIVES: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the com...
Neural Networks, Computer Machine Learning Electroencephalography Humans Sleep Stages Datasets as Topic Classification Polysomnography Sleep Apnea Syndromes Models, Biological Sleep
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Robotics in oral and maxillofacial surgery.

Annals of the Royal College of Surgeons of England May 1, 2018
How trans-oral robotic surgery can treat cancer in the oropharyngyal space
Blood Loss, Surgical Oropharyngeal Neoplasms Robotics Oropharynx Length of Stay Robotic Surgical Procedures Humans Sleep Apnea Syndromes Incidence Postoperative Complications Organ Sparing Treatments Time Factors Surgery, Oral
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