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@article{188024,
        author = {Prof Kavita Reddy and Swagath H and Shreya Gowda B A and Prajwal L Nadig and Tejaswini R R},
        title = {Oral cancer detection using AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {742-748},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188024},
        abstract = {Oral cancer is one of the top causes of cancer-related deaths worldwide. This is mainly due to late diagnosis and limited access to specialized healthcare. Early detection can greatly improve survival rates and lower treatment costs. Recent progress in artificial intelligence (AI), especially in deep learning and image processing, has changed how we diagnose cancer. This study brings together findings from various reviews and experimental works that examine the role of AI in detecting oral cancer. AI algorithms, particularly convolutional neural networks(CNNs),have shown impressive diagnostic accuracy, ranging from 81% to 99.7%. They have high sensitivity and specificity when distinguishing between normal, precancerous, and malignant lesions. AI systems that use photographic, cytological, and autofluorescence imaging allow for non-invasive and real-time screening. Some of these systems even work through smartphone apps, making them accessible in low-resource areas. Combining machine learning with telemedicine has shown good agreement with expert clinical evaluations, enabling remote and early diagnosis.},
        keywords = {Oral Cancer, Artificial Intelligence, Deep Learning, Convolutional Neural Network (CNN), Image Processing, Early Diagnosis, Computer Vision},
        month = {December},
        }