Otolaryngology

Patient-Centered Equitable and Safe Artificial Intelligence in Otolaryngology-Head and Neck Surgery.

The Ethics of Incorporating Artificial Intelligence Technologies in Prognostic Clinical Decision-Making in Otolaryngology.

Artificial Intelligence in Otolaryngology - Head and Neck Surgery in the Past Decade.

Artificial Intelligence in Head and Neck Surgery.

This article explores artificial intelligence's (AI's) role in otolaryngology for head and neck cancer diagnosis and management. It highlights AI's po...

Improving difficult direct laryngoscopy prediction using deep learning and minimal image analysis: a single-center prospective study.

Accurate prediction of difficult direct laryngoscopy (DDL) is essential to ensure optimal airway management and patient safety. The present study prop...

Variability of Guidelines and Disclosures for AI-Generated Content in Top Surgical Journals.

: When properly utilized, artificial intelligence generated content (AIGC) may improve virtually every aspect of research, from data gathering to synt...

Standardization, Collaboration, and Education in the Implementation of Artificial Intelligence in Otolaryngology: The Key to Scalable Impact.

The study delves into the crucial role of standardization, collaboration, and education in the integration of artificial intelligence (AI) in otolaryn...

Regulatory and Implementation Considerations for Artificial Intelligence.

Successful artificial intelligence (AI) implementation is predicated on the trust of clinicians and patients, and is achieved through a culture of res...

Artificial Intelligence in Otolaryngology: Topics in Epistemology & Ethics.

To fuel artificial intelligence (AI) potential in clinical practice in otolaryngology, researchers must understand its epistemic limitations, which ar...

Generative AI and Otolaryngology-Head & Neck Surgery.

The increasing development of artificial intelligence (AI) generative models in otolaryngology-head and neck surgery will progressively change our pra...

Laryngeal Cancer Screening During Flexible Video Laryngoscopy Using Large Computer Vision Models.

OBJECTIVE: Develop an artificial intelligence assisted computer vision model to screen for laryngeal cancer during flexible laryngoscopy.

The Use of Artificial Intelligence to Improve Readability of Otolaryngology Patient Education Materials.

OBJECTIVE: The recommended readability of health education materials is at the sixth-grade level. Artificial intelligence (AI) large language models s...

Transforming Otolaryngology-Head and Neck Surgery: The Pivotal Role of Artificial Intelligence in Clinical Workflows.

Use of artificial intelligence (AI) is expanding exponentially as it pertains to workflow operations. Otolaryngology-Head and Neck Surgery (OHNS), as ...

The Integration and Impact of Artificial Intelligence in Otolaryngology-Head and Neck Surgery: Navigating the Last Mile.

Incorporating artificial Intelligence and machine learning into otolaryngology requires careful data handling, security, and ethical considerations. S...

An automated approach for real-time informative frames classification in laryngeal endoscopy using deep learning.

PURPOSE: Informative image selection in laryngoscopy has the potential for improving automatic data extraction alone, for selective data storage and a...

Examining the Performance of ChatGPT 3.5 and Microsoft Copilot in Otolaryngology: A Comparative Study with Otolaryngologists' Evaluation.

To evaluate the response capabilities, in a public healthcare system otolaryngology job competition examination, of ChatGPT 3.5 and an internet-connec...

The role of artificial intelligence in training ENT residents: a survey on ChatGPT, a new method of investigation.

OBJECTIVE: The primary focus of this study was to analyze the adoption of ChatGPT among Ear, Nose, and Throat (ENT) trainees, encompassing its role in...

Classification of laryngeal diseases including laryngeal cancer, benign mucosal disease, and vocal cord paralysis by artificial intelligence using voice analysis.

Voice change is often the first sign of laryngeal cancer, leading to diagnosis through hospital laryngoscopy. Screening for laryngeal cancer solely ba...

Can GPT-4 revolutionize otolaryngology? Navigating opportunities and ethical considerations.

Otolaryngologists can enhance workflow efficiency, provide better patient care, and advance medical research and education by integrating artificial i...

Machine Learning for Predictive Analysis of Otolaryngology Residency Letters of Recommendation.

INTRODUCTION: Letters of recommendation (LORs) are a highly influential yet subjective and often enigmatic aspect of the residency application process...