Deep Learning Applied in Dentistry: Challenges and Prospects

Dear Colleagues,

The integration of engineering, artificial intelligence (AI), and clinical dental practice is revolutionizing the field of modern dentistry. Among the most transformative developments is the application of deep learning techniques, which are enhancing diagnostic accuracy, treatment planning, and patient-specific interventions. This Special Issue aims to explore the intersection of AI-driven technologies with dental science, particularly focusing on image analysis, predictive modeling, and guided surgery systems.

Deep learning models, such as convolutional neural networks (CNNs) and transformer architectures, are now being used to detect pathologies from radiographs, segment anatomical structures in 3D scans, and optimize surgical workflows through real-time decision support. These advancements are made possible through interdisciplinary collaboration between dental clinicians, biomedical engineers, and computer scientists. Despite notable progress, significant challenges remain in terms of data standardization, model interpretability, and clinical validation. This Special Issue welcomes original research, reviews, and case studies that push the boundaries of how AI can safely and effectively be integrated into dental and surgical practice.

Dr. María Prados-Privado
Guest Editor

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