Estimating the Severity of Oral Lesions Via Analysis of Cone Beam Computed Tomography Reports: A Proposed Deep Learning Model
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...
Saved in:
Main Authors: | Sare Mahdavifar, Seyed Mostafa Fakhrahmad, Elham Ansarifard |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-02-01
|
Series: | International Dental Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S0020653924001680 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Modeling dose uncertainty in cone-beam computed tomography: Predictive approach for deep learning-based synthetic computed tomography generation
by: Cédric Hémon, et al.
Published: (2025-01-01) -
Prevalence of Oral Lesions Biopsies Among Different Laboratories
by: Layla Muhamad
Published: (2024-12-01) -
Prevalence and predictive risk factor analysis of potentially malignant oral mucosal lesions among gond tribes of Bhopal
by: P. Arathi Menon, et al.
Published: (2025-01-01) -
Oral lesions and disorders and their prevalence arising from the use of illicit drugs in a prison population.
by: Marta Relvas, et al.
Published: (2025-01-01) -
The role of radiomics in dentistry and oral
radiology
by: Tannishtha ., et al.
Published: (2024-05-01)