Latest AI and machine learning research in otolaryngology for healthcare professionals.
INTRODUCTION: larynGuide™ is a novel assistive software integrated with the C-MAC® videolaryngoscope, which provides guidance during laryngoscopy and advises on tracheal tube position. This first in-human study evaluated the accuracy and reliability of larynGuide compared with the judgment of the airway operator. METHODS: This prospective, single-centre, investigator-initiated, observational study...
OBJECTIVE: Researchers in otolaryngology-head and neck surgery (OHNS) have sought to explore the potential of large language models (LLMs), but many publications do not include crucial information, such as prompting approach and model parameters. This has substantial implications for reproducibility, since LLMs can generate different output based on differences in "prompt engineering." We aimed to...
OBJECTIVES: Major advancements have been made in applying artificial intelligence and computer vision to analyze videolaryngoscopy data. These models ...
Nasal obstruction has multiple causes requiring specialist endoscopy for diagnosis. A rule-based expert system (RB-ES), which applies five "if-then" r...
This study aims to enhance the dosimetry accuracy in I planar imaging by utilizing a single oblique view and Monte Carlo (MC) validated dose point ker...
OBJECTIVE: This study aims to trends in female authorship in poster and oral presentations at American Academy of Otolaryngology-Head and Neck Surgery...
PURPOSE: Facial recognition of reconstructed computed tomography (CT) scans poses patient privacy risks, necessitating reliable facial de-identificati...
OBJECTIVE: Artificial Intelligence (AI) research needs to be clinician led; however, expertise typically lies outside their skill set. Collaborations ...
BACKGROUND: Volumetric atlases are an invaluable tool in neuroscience and otolaryngology, greatly aiding experiment planning and surgical intervention...
Event cameras respond to changes in log-brightness at the millisecond level, making them ideal for optical flow estimation. However, existing datasets...
OBJECTIVE: Traditional evaluations of surgical skills in otolaryngology rely heavily on subjective assessments, which are prone to variability and bia...
OBJECTIVE: To develop and evaluate the effectiveness of domain-specific customization in large language models (LLMs) by assessing the performance of ...
OBJECTIVE: To review the current literature on the applications of natural language processing (NLP) within the field of otolaryngology.
OBJECTIVES: Since the release of ChatGPT-4 in March 2023, large language models (LLMs) application in biomedical manuscript production has been widesp...
PURPOSE: This study aimed to explore the capabilities of advanced large language models (LLMs), including OpenAI's GPT-4 variants, Google's Gemini ser...
OBJECTIVES: ChatGPT is one of the most publicly available artificial intelligence (AI) softwares. Ear, nose and throat (ENT) services are often stretc...
BACKGROUND AND OBJECTIVES: Recently, artificial intelligence (AI) has been applied to otolaryngology. However, existing supervised learning methods ca...
BACKGROUND: Emergency endotracheal intubation is a critical skill for managing airway emergencies in the emergency department (ED). Accurate predictio...
Foundation models (FMs) are general-purpose artificial intelligence (AI) neural networks trained on massive datasets, including code, text, audio, ima...
Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating dopamine in the SN per compacta. Electroencephalogr...