Artificial Intelligence in Head and Neck Cancer Diagnosis: A Comprehensive Review with Emphasis on Radiomics, Histopathological, and Molecular Applications

This article highlights how artificial intelligence (AI) is revolutionizing the diagnosis and treatment of head and neck cancers (HNCs). This article explores the use of various AI techniques, including machine learning (ML), deep learning (DL), and convolutional neural networks (CNNs), in medical imaging, molecular profiling, and predictive modeling. AI has demonstrated improved accuracy in analyzing CT, MRI, and PET scans, often surpassing human radiologists. It is also applied to histopathology, automating the analysis of whole-slide images and assisting in tumor grading and segmentation. Additionally, AI aids in molecular analysis, particularly in mutation detection and treatment personalization. While AI shows promising results in enhancing diagnostic precision and workflow efficiency, challenges such as data standardization and model transparency still remain.