Review

Year : 2026 | Volume : 10 | Issue : 1 | Page : 14-17

Artificial Intelligence in Oral Cancer Histopathology: Current Applications and Future Perspectives

Review

1*Department of Pathology, Junior Research Fellow, Central Institute of Dental Sciences, New Delhi -110026, India.

Email: arjunmehta9593@gmail.com

Abstract

Introduction: Oral squamous cell carcinoma (OSCC) remains a major oral malignancy, and its histopathological diagnosis is often challenged by inter-observer variability. Artificial intelligence (AI), particularly machine learning and deep learning approaches, has emerged as a promising tool for improving diagnostic accuracy and reproducibility in oral pathology. To review the current applications of AI in oral cancer histopathology and evaluate its role in diagnosis, grading, prognostic prediction, and assessment of oral potentially malignant disorders. Materials and Methods: A narrative review of recent literature was conducted to examine AI-based technologies, including machine learning and deep learning models, used in the analysis of digital histopathological images of oral lesions and OSCC. Results: AI-assisted systems demonstrated promising performance in oral cancer detection, histological grading, prognostic prediction, and evaluation of oral potentially malignant disorders. These technologies improved diagnostic consistency, facilitated image analysis, and supported clinical decision-making. However, challenges related to data quality, algorithm transparency, standardization, and regulatory approval remain significant barriers to widespread clinical implementation. Conclusion: AI has considerable potential to enhance the accuracy, efficiency, and reproducibility of oral cancer diagnosis and management. Continued advancements in AI technologies and collaborative efforts among pathologists, clinicians, and data scientists are essential for successful integration into routine oral pathology practice.

Acknowledgment

Nil

Conflict of interest

Nil

Source of funding

Nil

How to cite this article: Arjun Mehta,Artificial Intelligence in Oral Cancer Histopathology: Current Applications and Future Perspectives, Int J Clinicopathol Correl. 2026; 10(1):14-17. 10.56501/Int.J.Clin.Pathol.Correl.10.1.ijcc0138. Copyright © 2026 Arjun Mehta.