Recent advancements in diagnosis of oral cancer

Key Points

• The study aims to explore recent technologies and methods for the diagnosis of oral cancer and their potential to improve early detection.
• Conducted a comprehensive literature review from 2015 to 2025 across multiple databases including PubMed, Scopus, and Web of Science.
• Evaluated various non-invasive diagnostic techniques such as optical coherence tomography (OCT), narrow-band imaging, and autofluorescence.
• Assessed the role of salivary biomarkers like IL-8, Cyfra 21-1, and miRNAs in diagnosis.
• Investigated the application of AI and digital pathology in enhancing image analysis and triage processes.
• Explored the potential of telemedicine in increasing access to diagnostic services.
• Non-invasive methods such as OCT and narrow-band imaging show significant potential in early oral cancer detection.
• Salivary biomarkers IL-8 and Cyfra 21-1 are promising indicators for diagnosing oral cancer.
• AI technologies, particularly convolutional neural networks (CNNs), improve the accuracy of image interpretation.
• Telemedicine offers enhanced access to diagnostic services, facilitating early detection.
• Integrating these technologies could lead to reduced mortality rates associated with oral cancer.