Latest AI and machine learning research in otolaryngology for healthcare professionals.
BACKGROUND: Intraoperative preservation of parathyroid glands (PGs) remained a significant challenge in thyroidectomy. Recently, deep learning has demonstrated considerable potential in medical applications. We proposed a novel intraoperative method for PG identification. METHODS: We developed a localization subnet based on YOLOX and a novel semantic segmentation model termed Trans-U-HRNet, collec...
The discovery of new organic photocatalysts (PCs) for energy transfer (EnT) catalysis remains a significant challenge, largely due to the vast and underexplored chemical space and the delicate balance of the photocatalytic properties. While transition-metal catalysts are effective, their high cost and environmental impact necessitate the development of metal-free alternatives. In this work, we pre...
OBJECTIVE: Improved operating room (OR) efficiency provides greater patient throughput, reduced costs, and maximal patient care. The aim of this study...
IMPORTANCE: Large language models (LLMs), a rapidly advancing domain of artificial intelligence (AI), are poised to transform administrative, clinical...
BACKGROUND: Aspiration causes or aggravates a variety of respiratory diseases. Subjective bedside evaluations of aspiration are limited by poor inter-...
OBJECTIVE: To develop and evaluate a deep learning object detection system for identifying vocal fold polyps in stroboscopic video frames using You On...
BACKGROUND: Rhinoplasty is a complex operation that warrants careful consideration of both functional and aesthetic principles. Despite its prevalence...
OBJECTIVES: To develop and validate a multimodal deep learning model integrating clinical data, contrast-enhanced CT, and laryngoscopic images for dif...
OBJECTIVE: To compare the diagnostic accuracy, linguistic clarity, and user satisfaction of three large language models (ChatGPT-4.0, Claude 3.7 Sonet...
Deep learning (DL) applications in healthcare are expanding beyond proof-of-concept studies. Yet, the extent of its real-world implementation and impa...
PURPOSE: Artificial intelligence systems known as large language models are being evaluated for clinical decision support, yet their role in emergency...
Operative ear, nose and throat (ENT) medicine in Germany is facing a profound structural change, which is significantly influenced by the ongoing hosp...
INTRODUCTION: larynGuide™ is a novel assistive software integrated with the C-MAC® videolaryngoscope, which provides guidance during laryngoscopy and ...
OBJECTIVE: Researchers in otolaryngology-head and neck surgery (OHNS) have sought to explore the potential of large language models (LLMs), but many p...
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...