Automated 2-Dimensional Measurement of Vestibular Schwannoma: Validity and Accuracy of an Artificial Intelligence Algorithm.

Olaf M Neve Stephan R Romeijn Yunjie Chen Larissa Nagtegaal Willem Grootjans Jeroen C Jansen Marius Staring Berit M Verbist Erik F Hensen

Published in: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery (2023)

Automated 2D diameter measurements and growth detection of vestibular schwannomas are at least as accurate as human 2D measurements. In clinical practice, measurements of the maximal extrameatal tumor (2D) diameters of vestibular schwannomas provide important complementary information to total tumor volume (3D) measurements. Combining both in an automated measurement algorithm facilitates clinical adoption.

Keyphrases

machine learning
artificial intelligence
deep learning
big data
clinical practice
endothelial cells
hearing loss
high resolution
healthcare
heart rate
resistance training
mass spectrometry
neural network
loop mediated isothermal amplification
single cell
high intensity
social media
optical coherence tomography