AIMC Topic: Apnea

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SLEEP-SEE-THROUGH: Explainable Deep Learning for Sleep Event Detection and Quantification From Wearable Somnography.

IEEE journal of biomedical and health informatics Jun 30, 2023
Evidence is rapidly accumulating that multifactorial nocturnal monitoring, through the coupling of wearable devices and deep learning, may be disruptive for early diagnosis and assessment of sleep disorders. In this work, optical, differential air-pr...
Humans Deep Learning Wearable Electronic Devices Sleep Snoring Polysomnography Apnea
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Automatic unsupervised respiratory analysis of infant respiratory inductance plethysmography signals.

PloS one Sep 11, 2020
Infants are at risk for potentially life-threatening postoperative apnea (POA). We developed an Automated Unsupervised Respiratory Event Analysis (AUREA) to classify breathing patterns obtained with dual belt respiratory inductance plethysmography an...
Humans Female Male Postoperative Complications Infant Unsupervised Machine Learning Signal Processing, Computer-Assisted Respiratory Mechanics Plethysmography Apnea
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Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.

Artificial intelligence in medicine Jul 25, 2019
OBJECTIVE: The neonatal period of a child is considered the most crucial phase of its physical development and future health. As per the World Health Organization, India has the highest number of pre-term births [1], with over 3.5 million babies born...
Humans Neural Networks, Computer Algorithms Infant, Newborn Infant, Extremely Premature Deep Learning India Support Vector Machine Decision Trees Birth Weight Heart Rate Datasets as Topic Infant, Premature Gestational Age Intensive Care Units, Neonatal Clinical Decision Rules Apnea
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