The Role of Artificial Intelligence in Oral Cancer: A Review of Current Applications and Future Directions

Abstract

Oral cancer remains a major global health concern with high morbidity and mortality, largely due to delays in detection and challenges in accurate diagnosis. Traditional methods such as visual examination, biopsy, and histopathological review can be time-consuming, subjective, and limited by clinician experience. In recent years, artificial intelligence has shown promise in improving the accuracy and efficiency of oral cancer care. Deep learning models support early detection by identifying suspicious lesions on clinical photographs and histopathology images, while digital pathology systems help reduce inter-observer variability. AI-based tools are also contributing to risk assessment, prognosis prediction, and treatment planning, including radiotherapy dose optimization and surgical margin evaluation. Mobile health applications and wearable devices enhance patient monitoring and support long-term follow-up by identifying changes that may indicate recurrence. Despite these advances, concerns related to data quality, model transparency, privacy, and regulatory approval remain barriers to widespread adoption. Looking ahead, integrating imaging, clinical data, and molecular information may enable more personalized treatment strategies. With careful clinical validation and responsible implementation, AI has the potential to complement clinician judgment and improve outcomes across the oral cancer care continuum.