AIMC Topic: Intubation, Intratracheal
Clear Filters Showing 41 to 50 of 51 articles
Comparison of Coopdech®, CoPilot®, Intubrite®, and Macintosh laryngoscopes for tracheal intubation during pediatric cardiopulmonary resuscitation: a randomized, controlled crossover simulation trial.
European journal of pediatrics
May 21, 2015
UNLABELLED: The aim of the study was to compare the intubation times and success rates of various laryngoscopes during resuscitation in pediatric emergency intubation with uninterrupted chest compression on a standardized pediatric manikin model. Thi...
Comparing Artificial Intelligence-Based Versus Conventional Endotracheal Tube Monitoring Systems in Clinical Practice.
Studies in health technology and informatics
Jul 24, 2024
Endotracheal tube dislodgement is a common patient safety incident in clinical settings. Current clinical practices, primarily relying on bedside visual inspections and equipment checks, often fail to detect endotracheal tube displacement or dislodge...
Development and validation of an artificial intelligence algorithm for detecting vocal cords in video laryngoscopy.
Medicine
Dec 22, 2023
Airway procedures in life-threatening situations are vital for saving lives. Video laryngoscopy (VL) is commonly performed during endotracheal intubation (ETI) in the emergency department. Artificial intelligence (AI) is widely used in the medical fi...
Individualized Treatment Effects: Machine Learning Can Revolutionize Observations, but Let's Understand What We Are Observing.
American journal of respiratory and critical care medicine
Jun 15, 2023
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...
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).
Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach.
Respiratory care
Sep 1, 2020
BACKGROUND: Bedside monitors in the ICU routinely measure and collect patients' physiologic data in real time to continuously assess the health status of patients who are critically ill. With the advent of increased computational power and the abilit...
Automated Assessment System for Neonatal Endotracheal Intubation Using Dilated Convolutional Neural Network.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Neonatal endotracheal intubation (ETI) is an important, complex resuscitation skill, which requires a significant amount of practice to master. Current ETI practice is conducted on the physical manikin and relies on the expert instructors' assessment...
[Development of Motion Unit of Simulated Intelligent Endotracheal Suctioning Robot].
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Jan 30, 2019
A motion unit for sucking robot with a stable motion, convenient operation and process simulation is introduced. The key parameters and process data of the sucking operation were obtained from the clinical work, which provided the basis for the desig...
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