Towards precision dentistry through artificial intelligence and blockchain-based digital Twins: Investigating challenges and solution strategies

Abstract

The integration of artificial intelligence (AI), blockchain, and digital twins (DT) in dentistry is essential to meet evolving patient expectations and global healthcare challenges. However, realizing their full potential requires addressing significant adoption barriers. While conceptual studies have explored challenges to implementing AI, blockchain, and DT in dentistry, no prior research has systematically analyzed the interrelationships among these obstacles using a structured decision framework. This study employs pentagonal fuzzy (PF) DEMATEL to investigate the connections among challenges to effectively implementing AI and blockchain-based DT in dentistry. Expert opinions highlight ethical considerations and bias and fairness in AI-based DT as the most critical causal challenges. We propose an AI and blockchain-based DT architecture that enables human doctors to leverage DT-based decision support, while AI-driven systems execute high-precision procedures with blockchain verified workflows. This framework enhances treatment accuracy and personalization in dentistry and offers a scalable model for addressing societal concerns, such as privacy, fairness, and labor dynamics, in technology driven ecosystems. A pilot study framework is proposed to validate diagnostic accuracy, data security, and treatment customization. Accompanied by stakeholder guidelines, this research bridges dentistry with broader discussions on technology’s societal impact, emphasizing the need for interdisciplinary strategies to ensure equitable and trustworthy innovation.