Large AI Models in Dental Healthcare (arxiv.org)

Recent research highlights the emerging role of large-scale AI models in dental healthcare, a field that impacts nearly 3.5 billion people globally. This systematic review categorizes AI models into three key types: language-generative models, discriminative vision foundation models, and dental-specific foundation models. The findings indicate that while language models excel in text-based tasks like clinical reasoning and patient communication, their performance in image diagnostics is inconsistent. In contrast, specialized models, such as DentVFM and OralGPT, have shown superior capabilities in handling complex, multimodal tasks. The significance of these developments lies in their potential to enhance dental diagnosis and treatment through effective integration of diverse AI systems. The research underscores the need for collaborative frameworks that combine general-purpose and dental-specific models in structured pipelines for optimal outcomes. However, challenges such as data scarcity, particularly in annotated dental datasets, and issues with model hallucination must be addressed for safe deployment in clinical settings. This study paves the way for a more nuanced understanding of AI's role in dentistry and suggests a future where AI-driven solutions significantly improve patient care in oral health.