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Trachea

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[Effect of location and type of exhalation valve on carbon dioxide rebreathing during noninvasive positive pressure ventilation: a experimental study].

Zhonghua wei zhong bing ji jiu yi xue 27132439
OBJECTIVE: To investigate the influence of exhalation valve location as well as its type on carbon dioxide (CO2) rebreathing during noninvasive positive pressure ventilation (NPPV).
Carbon Dioxide Exhalation Humans Masks Noninvasive Ventilation Positive-Pressure Respiration Tidal Volume Trachea
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Minimally Invasive Surgical Approach for Posterior Tracheopexy to Treat Severe Tracheomalacia: Lessons Learned from Initial Case Series.

Journal of laparoendoscopic & advanced surgical techniques. Part A 29975595
Posterior tracheopexy directly addresses membranous tracheal intrusion in severe tracheomalacia (TM). We have previously reported our experience of posterior tracheopexy through open approach in a large series of patients. This study aimed to review...
Adolescent Child Child, Preschool Female Humans Infant Male Postoperative Period Retrospective Studies Robotics Severity of Illness Index Thoracic Surgery, Video-Assisted Trachea Tracheomalacia Young Adult
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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 31482834
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...
Deep Learning Female Humans Male Middle Aged Neural Networks, Computer Polysomnography Reproducibility of Results Respiratory Sounds Sensitivity and Specificity Sleep Apnea Syndromes Trachea
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A Convolutional Neural Network for Real Time Classification, Identification, and Labelling of Vocal Cord and Tracheal Using Laryngoscopy and Bronchoscopy Video.

Journal of medical systems 31897740
BACKGROUND: The use of artificial intelligence, including machine learning, is increasing in medicine. Use of machine learning is rising in the prediction of patient outcomes. Machine learning may also be able to enhance and augment anesthesia clinic...
Adolescent Algorithms Bronchoscopy Child Child, Preschool Female Humans Infant Laryngoscopy Machine Learning Male Neural Networks, Computer Sensitivity and Specificity Trachea Vocal Cords Young Adult
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Automated labeling of the airway tree in terms of lobes based on deep learning of bifurcation point detection.

Medical & biological engineering & computing 32613598
This paper presents an automatic lobe-based labeling of airway tree method, which can detect the bifurcation points for reconstructing and labeling the airway tree from a computed tomography image. A deep learning-based network structure is designed ...
Algorithms Bronchi Computational Biology Computer Simulation Deep Learning Humans Imaging, Three-Dimensional Lung Models, Anatomic Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Trachea
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A comparison of regularized logistic regression and random forest machine learning models for daytime diagnosis of obstructive sleep apnea.

Medical & biological engineering & computing 32803448
A major challenge in big and high-dimensional data analysis is related to the classification and prediction of the variables of interest by characterizing the relationships between the characteristic factors and predictors. This study aims to assess ...
Adolescent Adult Aged Breath Tests Databases, Factual Diagnosis, Computer-Assisted Female Humans Logistic Models Machine Learning Male Middle Aged Signal Processing, Computer-Assisted Sleep Apnea, Obstructive Trachea Wakefulness Young Adult
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Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study.

PloS one 34473775
OBJECTIVE: To construct a prediction model for optimal tracheal tube depth in pediatric patients using machine learning.
Child Child, Preschool Humans Infant Intubation, Intratracheal Machine Learning Retrospective Studies Trachea
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Using Deep Learning Segmentation for Endotracheal Tube Position Assessment.

Journal of thoracic imaging 34292275
PURPOSE: The purpose of this study was to determine the efficacy of using deep learning segmentation for endotracheal tube (ETT) position on frontal chest x-rays (CXRs).
Deep Learning Humans Intubation, Intratracheal Reproducibility of Results Retrospective Studies Trachea
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