AIMC Topic: Laryngoscopy

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Real-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning.

The Laryngoscope
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
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
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
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
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
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...

Artificial Intelligence for Upper Aerodigestive Tract Endoscopy and Laryngoscopy: A Guide for Physicians and State-of-the-Art Review.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: The endoscopic and laryngoscopic examination is paramount for laryngeal, oropharyngeal, nasopharyngeal, nasal, and oral cavity benign lesions and cancer evaluation. Nevertheless, upper aerodigestive tract (UADT) endoscopy is intrinsically ...

Support of deep learning to classify vocal fold images in flexible laryngoscopy.

American journal of otolaryngology
PURPOSE: To collect a dataset with adequate laryngoscopy images and identify the appearance of vocal folds and their lesions in flexible laryngoscopy images by objective deep learning models.

Convolutional neural network based anatomical site identification for laryngoscopy quality control: A multicenter study.

American journal of otolaryngology
OBJECTIVES: Video laryngoscopy is an important diagnostic tool for head and neck cancers. The artificial intelligence (AI) system has been shown to monitor blind spots during esophagogastroduodenoscopy. This study aimed to test the performance of AI-...

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

Computers in biology and medicine
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...