Prediction of bone invasion of oral squamous cell carcinoma using a magnetic resonance imaging-based machine learning model.

Elif Meltem Aslan Ozturk Gürkan Ünsal Ferhat Erişir Kaan Orhan

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)

This study introduces an ML model utilizing SVM and radiomics to predict bone invasion in OSCC. Despite the promising results, the small sample size necessitates larger multicenter studies to validate and expand these findings.

Keyphrases

magnetic resonance imaging
machine learning
bone mineral density
cell migration
soft tissue
contrast enhanced
computed tomography
bone loss
clinical trial
cross sectional
postmenopausal women
diffusion weighted imaging