An Update on the Use of Artificial Intelligence in Digital Pathology for Oral Epithelial Dysplasia Research.

Journal: Head and neck pathology
PMID: 38727841

Abstract

INTRODUCTION: Oral epithelial dysplasia (OED) is a precancerous histopathological finding which is considered the most important prognostic indicator for determining the risk of malignant transformation into oral squamous cell carcinoma (OSCC). The gold standard for diagnosis and grading of OED is through histopathological examination, which is subject to inter- and intra-observer variability, impacting accurate diagnosis and prognosis. The aim of this review article is to examine the current advances in digital pathology for artificial intelligence (AI) applications used for OED diagnosis.

Authors

  • Shahd A Alajaji
    Department of Oncology and Diagnostic Sciences, School of Dentistry, University of Maryland Baltimore, MD, USA; Division of Artificial Intelligence Research, University of Maryland School of Dentistry, Baltimore, MD, USA; Department of Oral Medicine and Diagnostic Sciences, College of Dentistry, King Saud University, Riyadh, Saudi Arabia.
  • Zaid H Khoury
    Department of Oral Diagnostic Sciences and Research, Meharry Medical College School of Dentistry, Nashville, TN, USA.
  • Maryam Jessri
    Oral Health Centre of Western Australia, Perth, WA, Australia.
  • James J Sciubba
    Department of Otolaryngology, Head & Neck Surgery, The Johns Hopkins University, Baltimore, MD, USA.
  • Ahmed S Sultan
    School of Dentistry, University of Maryland, Baltimore, MD, USA.

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