Estimating the Severity of Oral Lesions Via Analysis of Cone Beam Computed Tomography Reports: A Proposed Deep Learning Model.

Journal: International dental journal
PMID: 39068121

Abstract

OBJECTIVES: Several factors such as unavailability of specialists, dental phobia, and financial difficulties may lead to a delay between receiving an oral radiology report and consulting a dentist. The primary aim of this study was to distinguish between high-risk and low-risk oral lesions according to the radiologist's reports of cone beam computed tomography (CBCT) images. Such a facility may be employed by dentist or his/her assistant to make the patient aware of the severity and the grade of the oral lesion and referral for immediate treatment or other follow-up care.

Authors

  • Sare Mahdavifar
    Dept. of Computer Science and Engineering and IT, Shiraz University, Shiraz, Iran.
  • Seyed Mostafa Fakhrahmad
    Dept. of Computer Science and Engineering and IT, Shiraz University, Shiraz, Iran.
  • Elham Ansarifard
    Dept. of Prosthodontics, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran; Biomaterials Research Center, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran. Electronic address: ansarifard@sums.ac.ir.

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