AIMC Topic: Trachea

Clear Filters Showing 11 to 20 of 20 articles

Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study.

PloS one Sep 2, 2021
OBJECTIVE: To construct a prediction model for optimal tracheal tube depth in pediatric patients using machine learning.
Humans Machine Learning Retrospective Studies Infant Child, Preschool Intubation, Intratracheal Child Trachea
View on PubMed DOI

A comparison of regularized logistic regression and random forest machine learning models for daytime diagnosis of obstructive sleep apnea.

Medical & biological engineering & computing Aug 17, 2020
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 Logistic Models Signal Processing, Computer-Assisted Sleep Apnea, Obstructive Male Middle Aged Diagnosis, Computer-Assisted Wakefulness Breath Tests Trachea Humans Machine Learning Databases, Factual Female Aged Young Adult Adult
View on PubMed DOI

Automated labeling of the airway tree in terms of lobes based on deep learning of bifurcation point detection.

Medical & biological engineering & computing Jul 2, 2020
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 ...
Radiographic Image Interpretation, Computer-Assisted Trachea Models, Anatomic Bronchi Deep Learning Imaging, Three-Dimensional Computational Biology Humans Algorithms Computer Simulation Tomography, X-Ray Computed Lung
View on PubMed DOI

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 Jan 2, 2020
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...
Humans Neural Networks, Computer Machine Learning Algorithms Female Young Adult Sensitivity and Specificity Vocal Cords Child, Preschool Laryngoscopy Male Child Infant Bronchoscopy Adolescent Trachea
View on PubMed DOI

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 Jul 5, 2018
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...
Child Robotics Thoracic Surgery, Video-Assisted Postoperative Period Humans Severity of Illness Index Retrospective Studies Female Adolescent Trachea Young Adult Child, Preschool Male Tracheomalacia Infant
View on PubMed DOI

Use of Machine Learning Models to Predict Microaspiration Measured by Tracheal Pepsin A.

American journal of critical care : an official publication, American Association of Critical-Care Nurses Jan 1, 2025
BACKGROUND: Enteral feeding intolerance, a common type of gastrointestinal dysfunction leading to underfeeding, is associated with increased mortality. Tracheal pepsin A, an indicator of microaspiration, was found in 39% of patients within 24 hours o...
Humans Machine Learning Biomarkers Female Respiration, Artificial Aged Pepsin A Adult Enteral Nutrition Male Trachea Middle Aged
View on PubMed DOI

Validation of a Deep Learning-based Automatic Detection Algorithm for Measurement of Endotracheal Tube-to-Carina Distance on Chest Radiographs.

Anesthesiology Dec 1, 2022
BACKGROUND: Improper endotracheal tube (ETT) positioning is frequently observed and potentially hazardous in the intensive care unit. The authors developed a deep learning-based automatic detection algorithm detecting the ETT tip and carina on portab...
Trachea Intubation, Intratracheal Mediastinum Humans Adult Deep Learning Radiography
View on PubMed DOI

Using Deep Learning Segmentation for Endotracheal Tube Position Assessment.

Journal of thoracic imaging Mar 1, 2022
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 Trachea Intubation, Intratracheal Retrospective Studies Reproducibility of Results
View on PubMed DOI

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...
Sleep Apnea Syndromes Polysomnography Trachea Respiratory Sounds Neural Networks, Computer Male Female Humans Middle Aged Reproducibility of Results Deep Learning Sensitivity and Specificity
View on PubMed DOI

[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 Oct 1, 2015
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).
Trachea Carbon Dioxide Humans Exhalation Positive-Pressure Respiration Masks Tidal Volume Noninvasive Ventilation
View on PubMed
Popular Topics
Recent Journals