THE ROLE OF ARTIFICIAL INTELLIGENCE AND RADIOLOGICAL IMAGING TECHNOLOGIES IN THE EARLY DETECTION OF MAXILLOFACIAL TUMORS
Keywords:
artificial intelligence, maxillofacial tumors, radiology, early diagnosis, machine learning, CT, MRI, deep learning, oncology, diagnostic imagingAbstract
Early detection of maxillofacial tumors remains a critical challenge in modern medicine due to the anatomical complexity of the region and the often-asymptomatic nature of early-stage lesions. Recent advancements in artificial intelligence (AI) and radiological imaging technologies have significantly improved diagnostic accuracy and efficiency. This study aims to analyze the role of AI-based systems and modern imaging modalities in the early detection of maxillofacial tumors. A comprehensive review of recent literature and clinical data was conducted, focusing on diagnostic accuracy, sensitivity, and specificity of AI-assisted imaging techniques. The findings indicate that AI integration into radiology enhances early tumor detection, reduces diagnostic errors, and supports clinical decision-making. The study highlights the transformative potential of AI in maxillofacial oncology.
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