Harnessing AI for precision tonsillitis diagnosis: a revolutionary approach in endoscopic analysis.

Po-Hsuan Jeng Chien-Yi Yang Tien-Ru Huang Chung-Feng Jeffrey Kuo Shao-Cheng Liu

Published in: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery (2024)

Our research highlights the potential of using UNet for fully automated semantic segmentation of oropharyngeal structures, which aids in subsequent feature extraction, machine learning, and enables accurate AI diagnosis of tonsillitis. This innovation shows promise for enhancing both the accuracy and speed of tonsillitis assessments.

Keyphrases

machine learning
artificial intelligence
big data
deep learning
high resolution
ultrasound guided
antiretroviral therapy
risk assessment
human health
climate change
data analysis
single cell