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

Authors

  • Azam Jan Department of Mechatronics Engineering, University of Engineering and Technology, Peshawar, Pakistan
  • Shahzad Anwar Department of Mechatronics Engineering, University of Engineering and Technology, Peshawar, Pakistan
  • Rehmat Ullah * Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
  • Yunhi Zhu Qilu University of Technology (Shandong Academy of Science), Jinan, P.R China

DOI:

https://doi.org/10.63163/jpehss.v3i2.333

Keywords:

Dentistry, Digital Twin, Orthodontics, CAD/CAM, Machine Learning and Deep Learning

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.

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Published

2025-05-09

How to Cite

Azam Jan, Shahzad Anwar, Rehmat Ullah *, & Yunhi Zhu. (2025). Digital Twin in Dental Healthcare: Transforming Diagnostics, Surgery, and Patient Management. Physical Education, Health and Social Sciences, 3(2), 15–27. https://doi.org/10.63163/jpehss.v3i2.333