AIMC Topic: Laryngoscopy
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An automated approach for real-time informative frames classification in laryngeal endoscopy using deep learning.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
May 2, 2024
PURPOSE: Informative image selection in laryngoscopy has the potential for improving automatic data extraction alone, for selective data storage and a faster review process, or in combination with other artificial intelligence (AI) detection or diagn...
Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.
American journal of otolaryngology
Apr 30, 2024
OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL).
A review of the current status and progress in difficult airway assessment research.
European journal of medical research
Mar 13, 2024
A difficult airway is a situation in which an anesthesiologist with more than 5 years of experience encounters difficulty with intubation or mask ventilation. According to the 2022 American Society of Anesthesiologists Practice Guidelines for the Man...
Development of an Artificial Intelligence-Based Image Recognition System for Time-Sequence Analysis of Tracheal Intubation.
Anesthesia and analgesia
Feb 21, 2024
BACKGROUND: Total intubation time (TIT) is an objective indicator of tracheal intubation (TI) difficulties. However, large variations in TIT because of diverse initial and end targets make it difficult to compare studies. A video laryngoscope (VLS) c...
Real-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning.
The Laryngoscope
Jan 4, 2024
OBJECTIVE: To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos.
The Use of Deep Learning Software in the Detection of Voice Disorders: A Systematic Review.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jan 3, 2024
OBJECTIVE: To summarize the use of deep learning in the detection of voice disorders using acoustic and laryngoscopic input, compare specific neural networks in terms of accuracy, and assess their effectiveness compared to expert clinical visual exam...
Deep learning-based facial analysis for predicting difficult videolaryngoscopy: a feasibility study.
Anaesthesia
Dec 13, 2023
While videolaryngoscopy has resulted in better overall success rates of tracheal intubation, airway assessment is still an important prerequisite for safe airway management. This study aimed to create an artificial intelligence model to identify diff...
Real-time detection of laryngopharyngeal cancer using an artificial intelligence-assisted system with multimodal data.
Journal of translational medicine
Oct 7, 2023
BACKGROUND: Laryngopharyngeal cancer (LPC) includes laryngeal and hypopharyngeal cancer, whose early diagnosis can significantly improve the prognosis and quality of life of patients. Pathological biopsy of suspicious cancerous tissue under the guida...
A deep learning pipeline for automated classification of vocal fold polyps in flexible laryngoscopy.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Sep 11, 2023
PURPOSE: To develop and validate a deep learning model for distinguishing healthy vocal folds (HVF) and vocal fold polyps (VFP) on laryngoscopy videos, while demonstrating the ability of a previously developed informative frame classifier in facilita...
Assessment of stress response due to C-Mac D-blade guided videolaryngoscopic endotracheal intubation and docking of da Vinci surgical robot using perfusion index in patients undergoing transoral robotic oncosurgery.
Journal of clinical monitoring and computing
Apr 24, 2023
Clinical utility of perfusion index (PI) has entered a new realm as a non-invasive, quantitative index of stress response to endotracheal intubation. Transoral robotic surgery (TORS) involves F-K retractor aided docking of the surgical robot producin...
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