AIMC Topic: Intubation, Intratracheal

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Critical element prediction of tracheal intubation difficulty: Automatic Mallampati classification by jointly using handcrafted and attention-based deep features.

Computers in biology and medicine Oct 4, 2022
Preoperative assessment of the difficulty of tracheal intubation is of great importance in anesthesia practice because failed intubation can lead to severe complications and even death. The Mallampati score is widely used as a critical assessment cri...
Artificial Intelligence Anesthesia Laryngoscopy 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.
Algorithms Humans Deep Learning Machine Learning Thyroid Gland Intubation, Intratracheal
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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.
Humans Neural Networks, Computer Artificial Intelligence Retrospective Studies Trachea Intubation, Intratracheal
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Selective Lobar Exclusion in Robot-Assisted-Thoracic Surgery Using EZ Blocker.

Journal of cardiothoracic and vascular anesthesia Apr 5, 2022
One-Lung Ventilation Thoracic Surgical Procedures Thoracic Surgery Intubation, Intratracheal Robotics Thoracic Surgery, Video-Assisted Humans
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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.
Child, Preschool Machine Learning Child Retrospective Studies Trachea Humans Infant Intubation, Intratracheal
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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
Machine Learning Logistic Models Obesity Intubation, Intratracheal 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...
Early Warning Score Clinical Decision Rules Respiratory Insufficiency Patient Admission Machine Learning Intubation, Intratracheal COVID-19 Humans Middle Aged Hospitalization Respiration, Artificial Aged Retrospective Studies Hospitals Triage Male ROC Curve Female Emergency Service, Hospital Logistic Models SARS-CoV-2
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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.
Male Health Services Needs and Demand Middle Aged Intubation, Intratracheal Female Predictive Value of Tests Deep Learning Respiration, Artificial Humans Critical Care ROC Curve COVID-19 Hospitalization Prospective Studies Aged
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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...
Machine Learning Calibration Algorithms Intubation, Intratracheal Female Humans Middle Aged ROC Curve Hospitalization Cohort Studies Critical Care 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.
SARS-CoV-2 Hospitalization Aged Prognosis Retrospective Studies Female Middle Aged Respiration, Artificial Cohort Studies Predictive Value of Tests Aged, 80 and over Adult Male COVID-19 Algorithms Intubation, Intratracheal Humans Area Under Curve Supervised Machine Learning New York City
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