Artificial intelligence based vision transformer application for grading histopathological images of oral epithelial dysplasia: a step towards AI-driven diagnosis.

Journal: BMC cancer
PMID: 40281456

Abstract

BACKGROUND: This study aimed to classify dysplastic and healthy oral epithelial histopathological images, according to WHO and binary grading systems, using the Vision Transformer (ViT) deep learning algorithm-a state-of-the-art Artificial Intelligence (AI) approach and compare it with established Convolutional Neural Network models (VGG16 and ConvNet).

Authors

  • Mahdi Hadilou
    Research Center for Prevention of Oral and Dental Diseases, Baqiyatallah University of Medical Sciences, Tehran, Iran.
  • Nazanin Mahdavi
    Department of Oral and Maxillofacial Pathology, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran.
  • Elham Keykha
    Research Center for Prevention of Oral and Dental Diseases, School of Dentistry, Baqiyatallah University of Medical Sciences, Tehran, Iran. Dr.keykha@chmail.ir.
  • Ali Ghofrani
    Student Research Committee, Baqiyatallah University of Medical Sciences, Tehran, Iran.
  • Elahe Tahmasebi
    Research Center for Prevention of Oral and Dental Diseases, School of Dentistry, Baqiyatallah University of Medical Sciences, Tehran, Iran.
  • Masoud Arabfard
    Department of Bioinformatics, Kish International Campus University of Tehran, Kish, Iran.

Keywords

External Resources

Popular Topics
Recent Journals