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Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 10 No 5 (2026): Volume 10, Issue 5, May 2026 | Pages: 496-504
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 26-05-2026
Oral cancer is a life-threatening disease where early detection is critical for effective treatment and improved patient survival rates. Traditional diagnostic methods are often invasive, expensive, and dependent on expert interpretation, which limits accessibility in resource-constrained settings. This study proposes an AI-based deep learning framework utilizing Convolutional Neural Networks (CNNs) to analyze clinical and histological images of oral lesions for automated detection and classification. The model is trained on a curated dataset to identify distinguishing patterns between benign and malignant cases with high accuracy. By automating the diagnostic process, the system aims to assist healthcare professionals in early identification of oral cancer, reduce diagnostic delays, and alleviate the workload on medical experts. The proposed approach has the potential to enhance screening programs, particularly in underserved regions, and contribute to improved health outcomes in oral oncology.
Deep learning; Images Classification; Oral Cancer; Feature Extraction.
Ashphak Khan, Anamika Patil, Nikita Borse, & Ashwini Shinkar. (2026). AI-Powered Oral Cancer Detection System Using Deep Learning. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(5), 496-504. Article DOI https://doi.org/10.47001/IRJIET/2026.105069
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