Artificial intelligence (AI) in healthcare refers to the use of advanced algorithms and computational models to approximate human cognition in the analysis of complex medical data. Unlike traditional technologies, AI systems have the capacity to acquire information, process large datasets, learn from them, and generate well-defined, clinically meaningful outputs without continuous human intervention. These capabilities—powered primarily by machine learning and deep learning—enable the recognition of intricate patterns and the development of autonomous decision-making logic.
As dentistry transitions beyond conventional X-ray–based imaging into the era of AI-enhanced dental-dedicated MRI (ddMRI), the potential impact on diagnostics, treatment planning, and patient safety is transformative. ddMRI offers radiation-free, high-contrast visualization of soft tissues, pulpal structures, TMJ, and peri-implant tissues—domains where traditional imaging is limited. When combined with AI-driven reconstruction, segmentation, image quality enhancement, and automated diagnostic workflows, ddMRI stands poised to redefine the future of dental radiology.
This lecture will (1) explain the fundamental principles of deep learning, (2) discuss the integration of AI with emerging ddMRI technologies, (3) provide key technical requirements for implementing AI and blockchain systems in healthcare, and (4) present examples of successful AI applications in dentistry and dentomaxillofacial radiology, based on our recent clinical and research studies. The session will also explore how blockchain, NFTs, and IoT infrastructures may support secure data management and interoperability in next-generation dental imaging ecosystems.