AIMC Topic: Intubation, Intratracheal

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Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms.

Frontiers in public health Aug 10, 2022
BACKGROUND: In this paper, we examine whether machine learning and deep learning can be used to predict difficult airway intubation in patients undergoing thyroid surgery.
Thyroid Gland Intubation, Intratracheal Humans Machine Learning Algorithms Deep Learning
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Automated Endotracheal Tube Placement Check Using Semantically Embedded Deep Neural Networks.

Academic radiology May 27, 2022
RATIONALE AND OBJECTIVES: To develop artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest X-rays (CXRs) and evaluate whether it can move into clinical validation as a quality improvement tool.
Artificial Intelligence Retrospective Studies Trachea Intubation, Intratracheal Humans Neural Networks, Computer
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Selective Lobar Exclusion in Robot-Assisted-Thoracic Surgery Using EZ Blocker.

Journal of cardiothoracic and vascular anesthesia Apr 5, 2022
Robotics Thoracic Surgery, Video-Assisted Thoracic Surgical Procedures Thoracic Surgery Humans Intubation, Intratracheal One-Lung Ventilation
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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 Sep 2, 2021
OBJECTIVE: To construct a prediction model for optimal tracheal tube depth in pediatric patients using machine learning.
Humans Child, Preschool Machine Learning Child Trachea Retrospective Studies Intubation, Intratracheal Infant
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Constructing a prediction model for difficult intubation of obese patients based on machine learning.

Journal of clinical anesthesia Apr 12, 2021
Intubation, Intratracheal Machine Learning Logistic Models Obesity Humans
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A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation.

Journal of medical Internet research Feb 10, 2021
BACKGROUND: Predicting early respiratory failure due to COVID-19 can help triage patients to higher levels of care, allocate scarce resources, and reduce morbidity and mortality by appropriately monitoring and treating the patients at greatest risk f...
Emergency Service, Hospital Respiratory Insufficiency Patient Admission Intubation, Intratracheal Early Warning Score Hospitals Clinical Decision Rules ROC Curve Humans Logistic Models Male Machine Learning Triage Middle Aged COVID-19 Female Respiration, Artificial Retrospective Studies SARS-CoV-2 Hospitalization Aged
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Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation.

Chest Dec 17, 2020
BACKGROUND: Objective and early identification of hospitalized patients, and particularly those with novel coronavirus disease 2019 (COVID-19), who may require mechanical ventilation (MV) may aid in delivering timely treatment.
Hospitalization Aged Male Middle Aged COVID-19 Predictive Value of Tests Humans Prospective Studies Respiration, Artificial Critical Care Female Health Services Needs and Demand Deep Learning Intubation, Intratracheal ROC Curve
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Predicting the need for intubation in the first 24 h after critical care admission using machine learning approaches.

Scientific reports Dec 1, 2020
Early and accurate prediction of the need for intubation may provide more time for preparation and increase safety margins by avoiding high risk late intubation. This study evaluates whether machine learning can predict the need for intubation within...
Middle Aged Critical Care Humans Female Cohort Studies Calibration Machine Learning Hospitalization ROC Curve Intubation, Intratracheal Algorithms Aged Male
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Development of a machine learning algorithm to predict intubation among hospitalized patients with COVID-19.

Journal of critical care Nov 16, 2020
PURPOSE: The purpose of this study is to develop a machine learning algorithm to predict future intubation among patients diagnosed or suspected with COVID-19.
Humans COVID-19 Algorithms SARS-CoV-2 Hospitalization Aged Aged, 80 and over Prognosis Retrospective Studies Female Supervised Machine Learning Respiration, Artificial New York City Cohort Studies Adult Intubation, Intratracheal Predictive Value of Tests Male Area Under Curve Middle Aged
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Machine Learning in Laryngoscopy Analysis: A Proof of Concept Observational Study for the Identification of Post-Extubation Ulcerations and Granulomas.

The Annals of otology, rhinology, and laryngology Aug 14, 2020
OBJECTIVE: Computer-aided analysis of laryngoscopy images has potential to add objectivity to subjective evaluations. Automated classification of biomedical images is extremely challenging due to the precision required and the limited amount of annot...
Airway Extubation Intensive Care Units Ulcer Respiration, Artificial Humans Intubation, Intratracheal Laryngoscopy Image Processing, Computer-Assisted Neural Networks, Computer Larynx Proof of Concept Study Machine Learning Granuloma, Laryngeal
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