Latest AI and machine learning research in otolaryngology for healthcare professionals.
Artificial intelligence (AI) algorithms, particularly deep learning, are automatic and sophisticated methods that recognize complex patterns in imaging data providing high qualitative assessments. Several machine-learning and deep-learning models using imaging techniques have been recently developed and validated to predict difficult airways. Despite advances in AI modeling. In this review article...
Introducing deep learning technologies into the medical image processing field requires accuracy guarantee, especially for high-resolution images relayed through endoscopes. Moreover, works relying on supervised learning are powerless in the case of inadequate labeled samples. Therefore, for end-to-end medical image detection with overcritical efficiency and accuracy in endoscope detection, an ens...
BACKGROUND: The early diagnosis of glottic laryngeal cancer is the key to successful treatment, and machine learning (ML) combined with narrow-band im...
This report synthesizes the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) Task Force's guidance on the integration of artificial ...
OBJECTIVE: This study aimed to develop an artificial intelligence (AI) method to augment video laryngoscopy (VL) by automating the detection of the gl...
BACKGROUND: The early diagnosis of laryngeal cancer (LCA) is crucial for prognosis, driving our search for an accurate, precise, and sensitive deep le...
OBJECTIVE: To evaluate and compare the readability and quality of patient information generated by Chat-Generative Pre-Trained Transformer-3.5 (ChatGP...
PURPOSE: Laryngoscopy is routinely used for suspicious vocal cord lesions with limited performance. Accumulated studies have demonstrated the bright p...
OBJECTIVES: Here we describe the development and pilot testing of the first artificial intelligence (AI) software "copilot" to help train novices to c...
This study aimed to establish a deep learning-based predictive model for the prognosis of idiopathic sudden sensorineural hearing loss (SSNHL). Data f...
OBJECTIVE: To predict post-thyroidectomy complications in papillary thyroid microcarcinoma (PTMC) patients using a deep learning model based on preope...
BACKGROUND: Postoperative hypoparathyroidism is a major complication of thyroidectomy, occurring when the parathyroid glands are inadvertently damaged...
OBJECTIVE: We used machine learning to develop and validate a multivariable algorithm allowing the accurate and early prediction of postoperative hypo...
Artificial intelligence (AI), particularly deep learning, has revolutionized various fields through its ability to model complex, noisy systems with h...
Artificial intelligence (AI) studies show how to program computers to simulate human intelligence and perform data interpretation, learning, and adapt...
BACKGROUND: Prolonged hospital stays after pediatric surgeries, such as tonsillectomy and adenoidectomy, pose significant concerns regarding cost and ...
PURPOSE: This study delves into the broader implications of artificial intelligence (AI) text generation technologies, including large language models...
Robotic surgery is a growing field with increasing applications to patient care. With the rising use of artificial intelligence (AI), a new frontier e...
This article discusses the role of computer vision in otolaryngology, particularly through endoscopy and surgery. It covers recent applications of art...