Related Experiment Video
Updated: May 16, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
Current AI Applications and Challenges in Oral Pathology
Zaizhen Xu1, Alice Lin1, Xiaoyuan Han1
1Department of Biomedical Sciences, Arthur A. Dugoni School of Dentistry, University of the Pacific, 155 5th St., San Francisco, CA 94103, USA.
Abstract:
Artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL) techniques such as convolutional neural networks (CNNs) and natural language processing (NLP), has shown remarkable promise in image analysis and clinical documentation in oral pathology. In order to explore the transformative potential of artificial intelligence (AI) in oral pathology, this review highlights key studies demonstrating current AI's improvement in oral pathology, such as detecting oral diseases accurately and streamlining diagnostic processes. However, several limitations, such as data quality, generalizability, legal and ethical considerations, financial constraints, and the need for paradigm shifts in practice, are critically examined. Addressing these challenges through collaborative efforts, robust validation, and strategic integration can pave the way for AI to revolutionize oral pathology, ultimately improving patient outcomes and advancing the field.
Related Concept Videos
Assessment of the Mouth
Mouth Inspection
The inspection begins with visually examining the mouth for symmetry, color, and size.
Oral Cavity
Teeth: The teeth are the hardest structures in our bodies. Humans have two sets of teeth throughout their lifetime: deciduous (baby) teeth and permanent teeth. Each tooth consists of several parts: the crown (visible part), the root (embedded in the jaw), enamel (hard outer...

