Otolaryngology

In Reference to Now You See It, Now You Don't: Laryngoscopy Findings of Paradoxical Vocal Fold Motion.

Can a Rule-Based Expert System Diagnose Nasal Obstruction from Nasoendoscopy Videos?

Nasal obstruction has multiple causes requiring specialist endoscopy for diagnosis. A rule-based exp...

Machine learning combine with nomogram to guide the establishment of endoscopic assistant system for gasless transaxillary endoscopic thyroidectomy.

OBJECTIVE: To explore the influence related factors of endoscopic assistant in gasless transaxillary...

AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view.

This study aims to enhance the dosimetry accuracy in I planar imaging by utilizing a single oblique ...

Trends in Female Authorship at American Academy of Otolaryngology-HNS Annual Meetings From 2007 to 2022.

OBJECTIVE: This study aims to trends in female authorship in poster and oral presentations at Americ...

Manual and automated facial de-identification techniques for patient imaging with preservation of sinonasal anatomy.

PURPOSE: Facial recognition of reconstructed computed tomography (CT) scans poses patient privacy ri...

Development of an Open-Source Algorithm for Automated Segmentation in Clinician-Led Paranasal Sinus Radiologic Research.

OBJECTIVE: Artificial Intelligence (AI) research needs to be clinician led; however, expertise typic...

Volumetric atlas of the rat inner ear from microCT and iDISCO+ cleared temporal bones.

BACKGROUND: Volumetric atlases are an invaluable tool in neuroscience and otolaryngology, greatly ai...

Towards Anytime Optical Flow Estimation with Event Cameras.

Event cameras respond to changes in log-brightness at the millisecond level, making them ideal for o...

Artificial Intelligence in Surgical Training and Applications to Otolaryngology: A Scoping Review.

OBJECTIVE: Traditional evaluations of surgical skills in otolaryngology rely heavily on subjective a...

Domain-Specific Customization for Language Models in Otolaryngology: The ENT GPT Assistant.

OBJECTIVE: To develop and evaluate the effectiveness of domain-specific customization in large langu...

Applications of Natural Language Processing in Otolaryngology: A Scoping Review.

OBJECTIVE: To review the current literature on the applications of natural language processing (NLP)...

Harnessing advanced large language models in otolaryngology board examinations: an investigation using python and application programming interfaces.

PURPOSE: This study aimed to explore the capabilities of advanced large language models (LLMs), incl...

An Evaluation of Current Trends in AI-Generated Text in Otolaryngology Publications.

OBJECTIVES: Since the release of ChatGPT-4 in March 2023, large language models (LLMs) application i...

Can Artificial Intelligence Software be Utilised for Thyroid Multi-Disciplinary Team Outcomes?

OBJECTIVES: ChatGPT is one of the most publicly available artificial intelligence (AI) softwares. Ea...

Cooperative GAN: Automated tympanic membrane anomaly detection using a Cooperative Observation Network.

BACKGROUND AND OBJECTIVES: Recently, artificial intelligence (AI) has been applied to otolaryngology...

Performance of machine learning models in predicting difficult laryngoscopy in the emergency department: a single-centre retrospective study comparing with conventional regression method.

BACKGROUND: Emergency endotracheal intubation is a critical skill for managing airway emergencies in...

AI-Powered Laryngoscopy: Exploring the Future With Google Gemini.

Foundation models (FMs) are general-purpose artificial intelligence (AI) neural networks trained on ...

Significance of gender, brain region and EEG band complexity analysis for Parkinson's disease classification using recurrence plots and machine learning algorithms.

Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating d...

The Future of Artificial Intelligence Using Images and Clinical Assessment for Difficult Airway Management.

Artificial intelligence (AI) algorithms, particularly deep learning, are automatic and sophisticated...

Semi-Supervised Detection Model Based on Adaptive Ensemble Learning for Medical Images.

Introducing deep learning technologies into the medical image processing field requires accuracy gua...