Mucoepidermoid carcinoma: Enhancing diagnostic accuracy and treatment strategy through machine learning models and web-based prognostic tool.

Journal: Journal of stomatology, oral and maxillofacial surgery
Published Date: Dec 25, 2024

Abstract

BACKGROUND: Oral cancer, particularly mucoepidermoid carcinoma (MEC), presents diagnostic challenges due to its histological diversity and rarity. This study aimed to develop machine learning (ML) models to predict survival outcomes for MEC patients and pioneer a clinically accessible prognostic tool.

Authors

  • Sakhr Alshwayyat
    Faculty of Medicine, Jordan University of Science & Technology, Irbid, Jordan.
  • Hanan M Qasem
    Faculty of Dentistry, Jordan University of Science and Technology, Irbid, Jordan. Electronic address: hmqasem22@den.just.edu.jo.
  • Lina Khasawneh
    Department of Prosthodontics, Faculty of Dentistry, Jordan University of Science and Technology, Irbid, Jordan. Electronic address: lwkhasawnh@just.edu.jo.
  • Mustafa Alshwayyat
    Faculty of Medicine, Jordan University of Science & Technology, Irbid, Jordan.
  • Mesk Alkhatib
    Faculty of Medicine, University of Jordan, Amman, Jordan.
  • Tala Abdulsalam Alshwayyat
    Faculty of Medicine, Jordan University of Science & Technology, Irbid, Jordan.
  • Hamza Al Salieti
    Faculty of Dentistry, Jordan University of Science and Technology, Irbid, Jordan. Electronic address: hmalsalieti187@den.just.edu.jo.
  • Ramez M Odat
    Faculty of Medicine, Jordan University of Science & Technology, Irbid, Jordan.

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