The early detection of oral potentially malignant disorders (OPMDs) is critical for improving patient outcomes, as these conditions can precede the development of oral cancer. Advanced technologies like deep learning (DL) are transforming diagnostic practices by offering more accurate and efficient methods. DL models, especially convolutional neural networks (CNNs), have shown remarkable potential in analyzing various types of medical images to detect OPMDs with precision.

Clinical imaging techniques such as photographic analysis, autofluorescence imaging, exfoliative cytology, histopathological examination, and optical coherence tomography (OCT) benefit significantly from DL applications. For instance, smartphone-based imaging combined with DL algorithms can distinguish between benign lesions and OPMDs, providing a valuable tool in areas with limited resources. Similarly, AI-enhanced autofluorescence imaging highlights biochemical changes in tissues, enhancing diagnostic accuracy. In histopathological analysis, DL algorithms automate the identification of dysplastic features, reducing variability among experts. OCT, which offers high-resolution imaging, also benefits from AI-driven models that can analyze tissue changes in real-time.

Beyond diagnosis, AI models are being employed to predict the likelihood of malignant transformation in OPMDs. Machine learning techniques integrate clinical, histopathological, and imaging data to provide personalized risk assessments. This approach aids clinicians in making informed decisions and managing patient care more effectively. However, challenges remain in standardizing image datasets, ensuring consistent image quality, and addressing algorithm limitations. Future research should focus on developing multimodal AI systems that combine multiple data sources for more precise and personalized diagnoses.

Deep learning holds immense promise in revolutionizing the management of OPMDs. By integrating advanced AI technologies into clinical workflows, healthcare providers can enhance early detection and improve patient outcomes. As AI continues to evolve, it may play a pivotal role in preventing oral cancer, ultimately saving lives and promoting better health for all.