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

Ishwarya S MamidiMichael E DunhamLacey K AdkinsAndrew J McWhorterZhide FangBritney T Banh

Published in: The Annals of otology, rhinology, and laryngology (2024)

Our model is highly sensitive and adequately specific for laryngeal cancer screening. Segmentation helps endoscopists identify and describe potential lesions. Further optimization is required to enable the model's deployment in clinical settings for real-time annotation during flexible laryngoscopy.

Keyphrases

papillary thyroid
squamous cell
deep learning
convolutional neural network
squamous cell carcinoma
machine learning
risk assessment
high resolution
rna seq
human health
living cells
solid state
fluorescent probe