AI Medical Compendium Journal:
The Laryngoscope

Showing 21 to 30 of 64 articles

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.

Exploring the Role of Artificial Intelligence Chatbots in Preoperative Counseling for Head and Neck Cancer Surgery.

The Laryngoscope
OBJECTIVE: To evaluate the potential use of artificial intelligence (AI) chatbots, such as ChatGPT, in preoperative counseling for patients undergoing head and neck cancer surgery.

Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey.

The Laryngoscope
INTRODUCTION: Accuracy and validity of voice AI algorithms rely on substantial quality voice data. Although commensurable amounts of voice data are captured daily in voice centers across North America, there is no standardized protocol for acoustic d...

Intraoral Microscopic Versus Robot-Assisted Sialolithotomy and Sialendoscopy for Submandibular Stones.

The Laryngoscope
OBJECTIVE: Sialendoscopy has remained the standard of treatment for sialolithiasis; however, large stones impacted in the submandibular gland hilum often require an intra-oral combined approach.

Artificial Intelligence Governance and Otolaryngology-Head and Neck Surgery.

The Laryngoscope
This rapid communication highlights components of artificial intelligence governance in healthcare and suggests adopting key governance approaches in otolaryngology – head and neck surgery.

Single-Port Robotic Removal of a Submucosal Foreign Body in the Distal Hypopharynx.

The Laryngoscope
In this report, we present a 55-year-old female with cervical stenosis that underwent C5-C7 anterior cervical discectomy and fusion surgery complicated by hardware failure requiring removal. One screw remained after transcervical hardware removal due...

The Detection of Nasopharyngeal Carcinomas Using a Neural Network Based on Nasopharyngoscopic Images.

The Laryngoscope
OBJECTIVE: To construct and validate a deep convolutional neural network (DCNN)-based artificial intelligence (AI) system for the detection of nasopharyngeal carcinoma (NPC) using archived nasopharyngoscopic images.

Machine Learning Analysis of Physical Activity Data to Classify Postural Dysfunction.

The Laryngoscope
BACKGROUND: Machine learning (ML) analysis of biometric data in non-controlled environments is underexplored.

Efficacy and Safety of Minimally Invasive Thyroid Surgery: A Network Meta-Analysis.

The Laryngoscope
OBJECTIVES: Minimally invasive and remote surgical approaches for thyroid tumors have been developed primarily for cosmetic benefit. However, conventional meta-analysis could not provide comparative data between new techniques. This network meta-anal...