Automatic detection of temporomandibular joint osteoarthritis radiographic features using deep learning artificial intelligence. A Diagnostic accuracy study.

Journal: Journal of stomatology, oral and maxillofacial surgery
Published Date: Oct 31, 2024

Abstract

OBJECTIVE: The purpose of this study was to investigate the diagnostic performance of a neural network Artificial Intelligence model for the radiographic confirmation of Temporomandibular Joint Osteoarthritis in reference to an experienced radiologist.

Authors

  • Louloua Mourad
    Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Beirut Arab University, Tripoli, Lebanon.
  • Nayer Aboelsaad
    Oral Surgical Sciences Department, Faculty of Dentistry, Beirut Arab University, Beirut, Lebanon. Electronic address: n.mohamedaboelsaad@bau.edu.lb.
  • Wael M Talaat
    Department of Oral and Craniofacial Health Sciences, College of Dental Medicine, University of Sharjah, Sharjah, 27272, UAE. wtaha@sharjah.ac.ae.
  • Nada M H Fahmy
    Department of Oral and Maxillofacial Surgery, Arab Academy for Science, Technology & Maritime Transport, College of Dentistry, El Alamein, Egypt; PhD, Oral and Maxillofacial Surgery, Faculty of Dentistry, Alexandria University.
  • Hams H Abdelrahman
    Department of Pediatric Dentistry and Dental Public Health, Faculty of Dentistry, Alexandria University, Alexandria, Egypt.
  • Yehia El-Mahallawy
    Oral and Maxillofacial Surgery Department, Faculty of Dentistry, Alexandria University, Alexandria, Egypt. Electronic address: yehia.el-mahallawy@alexu.edu.eg.

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