Digital Twin in Dental Healthcare: Transforming Diagnostics, Surgery, and Patient Management

Abstract

Artificial Intelligence (AI) transformed dentistry by improving diagnostic accuracy, treatment planning, robotic-assisted operations, and administrative efficiency. Machine learning algorithms and transformer-based designs perform better in radiography analysis, automated lesion detection, and early dental disease diagnosis. Intelligent robotic systems are also improving implant placement, minimally invasive procedures, and surgical decision-making through real-time feedback in dental surgeries. Despite these advances, data dependencies, algorithmic biases, high implementation costs, and legal impediments hinder the integration of intelligent systems into dentistry. This paper analyses the role of smart technologies the integration of Digital Twin technology in dentistry offers real-time simulation of oral conditions, enabling precise diagnostics and predictive treatment planning. These virtual replicas of patients’ dental structures facilitate personalized care and continuous monitoring. Future advancements in intelligent dentistry will increasingly rely on DT to enhance training, optimize procedures, and improve clinical outcomes.