Evaluating large language model role as an artificial intelligence-driven support tool as virtual assistant in oral and maxillofacial surgery

Objectives: To assess the current applications and future potential of large language models (LLMs) as virtual assistants in oral and maxillofacial surgery practice. Methods: A narrative review of literature published since 2019 was performed, focusing on AI-driven decision support, multimodal diagnostics, educational applications, and predictive analytics within surgical dentistry. Results: LLM-based systems demonstrated promising performance in clinical decision support, patient communication, research assistance, and educational content generation. Integration with imaging modalities improved diagnostic efficiency, while predictive analytics enhanced treatment planning accuracy. Challenges included data reliability, regulatory concerns, and ethical considerations. Conclusions: LLMs offer substantial opportunities to improve workflow efficiency and clinical decision-making in oral and maxillofacial surgery. Specialty-specific validation and ethical governance frameworks are essential for safe implementation.