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Advancing Videolaryngoscopy Through Integrated Channel Technology: Technical Solutions for Common Clinical Challenges.
Anesth Analg
January 2025
Department of Anaesthesia and Perioperative Medicine Royal Brisbane and Women's Hospital, & The University of Queensland Brisbane, Queensland,
Advancing the utility of bedside airway assessment: Awake-check videolaryngoscopy.
Eur J Anaesthesiol
February 2025
From the Advanced Airway Fellow, St John's Hospital, Livingston, NHS Lothian (JLO), Consultant in Anaesthesia, St John's Hospital, Livingston, NHS Lothian (PAW, AFM), and Consultant in Anaesthesia, Western General Hospital, Edinburgh, NHS Lothian, UK (AFM).
Radiotherapy Effects on Airway Management in Patients with Nasopharyngeal Cancer.
Cancers (Basel)
November 2024
Department of Radiation Oncology, Medical Faculty Heidelberg, University Heidelberg, 69120 Heidelberg, Germany.
: At present, there is a paucity of data in the literature pertaining to the impact of radiotherapy (RT) on the success of tracheal intubation in patients with nasopharyngeal cancer (NPC). The aim of this study is to investigate the frequency of difficult tracheal intubation in patients with NPC following RT. : Patients with NPC who underwent RT followed by surgery between 2012 and April 2024 at the University Hospital Heidelberg were retrospectively analyzed.
View Article and Find Full Text PDFNew developments in the application of artificial intelligence to laryngology.
Curr Opin Otolaryngol Head Neck Surg
December 2024
Sean Parker Institute for the Voice, Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine.
Purpose Of Review: The purpose of this review is to summarize the existing literature on artificial intelligence technology utilization in laryngology, highlighting recent advances and current barriers to implementation.
Recent Findings: The volume of publications studying applications of artificial intelligence in laryngology has rapidly increased, demonstrating a strong interest in utilizing this technology. Vocal biomarkers for disease screening, deep learning analysis of videolaryngoscopy for lesion identification, and auto-segmentation of videofluoroscopy for detection of aspiration are a few of the new ways in which artificial intelligence is poised to transform clinical care in laryngology.
Comparative Analysis of Machine-Learning Model Performance in Image Analysis: The Impact of Dataset Diversity and Size.
Anesth Analg
December 2024
From the Department of Experimental Surgery, McGill University Health Center, Montreal, Quebec, Canada.
Background: This study presents an analysis of machine-learning model performance in image analysis, with a specific focus on videolaryngoscopy procedures. The research aimed to explore how dataset diversity and size affect the performance of machine-learning models, an issue vital to the advancement of clinical artificial intelligence tools.
Methods: A total of 377 videolaryngoscopy videos from YouTube were used to create 6 varied datasets, each differing in patient diversity and image count.
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