Artificial Intelligence and Deep Learning Frameworks for Automated Dental Disease Detection and Prosthodontic Treatment Planning
Artificial intelligence, Deep learning, Dental disease detection, Prosthodontic treatment planning, Digital dentistry
AuthorsAbstractArtificial intelligence (AI) and deep learning are transforming dentistry by enabling automated disease detection, improving diagnostic accuracy, and enhancing prosthodontic treatment planning through data-driven clinical decision support. This review comprehensively examines contemporary AI and deep learning frameworks for automated dental disease detection, emphasizing their applications, diagnostic performance, integration into digital prosthodontic workflows, current limitations, and future research directions. Advanced AI techniques, including convolutional neural networks, object detection algorithms, image segmentation networks, vision transformers, and generative AI models, have demonstrated high potential for identifying dental caries, periodontal disease, periapical lesions, tooth wear, fractures, and occlusal abnormalities from clinical and radiographic images. Integration with digital technologies such as CAD/CAM systems, intraoral scanners, facial scanning, virtual articulators, and cloud-based platforms has further improved personalized treatment planning, workflow efficiency, and clinical decision-making. However, challenges including limited dataset diversity, insufficient external validation, model explainability, ethical concerns, data privacy, and regulatory compliance continue to hinder widespread clinical implementation. AI is expected to become an indispensable decision-support tool in prosthodontics. Future research should prioritize transparent, interoperable, and clinically validated AI systems to advance safe, evidence-based, patient-centered digital dentistry worldwide.
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