Application of Artificial Intelligence to Diagnosis of Laryngeal Lesions Using Laryngoscopy

Abstract

Laryngeal diseases have a significant impact on quality of life and often require timely and accurate diagnosis for effective management. Conventional methods of diagnosis, such as manual inspection of laryngoscopic images, have limitations in terms of accuracy and efficiency. The integration of artificial intelligence (AI) and machine learning techniques in laryngoscopic image analysis has emerged as a promising approach to enhance diagnostic accuracy, streamline workflow, and improve patient outcomes. This review paper provides an in-depth analysis of the recent advancements in AI-driven laryngoscopic image analysis for the diagnosis of laryngeal diseases, also covering methodologies, challenges, and future prospects.