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

Journal: 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
PMID: 39083062

Abstract

OBJECTIVES: Radiomics, a recently developed image-processing technology, holds potential in medical diagnostics. This study aimed to propose a machine-learning (ML) model and evaluate its effectiveness in detecting oral squamous cell carcinoma (OSCC) and predicting bone metastasis using magnetic resonance imaging (MRI).

Authors

  • Elif Meltem Aslan Öztürk
    Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Lokman Hekim University, Ankara, Turkey. aslan.meltem5@gmail.com.
  • Gürkan Ünsal
    Faculty of Dentistry, Department of Dentomaxillofacial Radiology, Near East University, Nicosia, Cyprus.
  • Ferhat Erişir
    Department of Otorhinolaryngology and Head and Neck Surgery, Faculty of Medicine, Near East University, Kyrenia, Cyprus.
  • Kaan Orhan
    Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Dentomaxillofacial Radiologist, Ankara University, Ankara, Turkey.

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