Generative Pre-trained Transformer: Trends, Applications, Strengths and Challenges in Dentistry: A Systematic Review

Area of Science:

• Dentistry
• Artificial Intelligence
• Large Language Models (LLMs)

Background:

• Generative Pre-trained Transformer (GPT) architecture, a type of LLM, is increasingly applied across various fields, including dentistry.
• While GPT offers revolutionary potential in dental applications, its integration also presents significant challenges.
• Developing robust ethical frameworks and conducting ongoing research are crucial for responsible GPT deployment in clinical settings.

Purpose of the Study:

• To systematically review the current trends, applications, strengths, and challenges of using GPT in dentistry.
• To identify key areas for future research and development in dental AI.

Main Methods:

• A systematic review adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted.
• A comprehensive search of databases yielded 704 studies; 16 articles with detailed information on GPT in dentistry and robust methodology were included after screening.
• The Critical Appraisal Skills Programme (CASP) checklist was used to evaluate the methodological quality of the included research.

Main Results:

• From 91 articles on GPT in dentistry, 60 original research articles were analyzed after excluding editorials and narrative reviews.
• A total of 16 articles reporting positive findings and employing robust methodologies were selected for the review.
• The included studies indicate a range of applications and identified strengths of GPT in dentistry.

Conclusions:

• The current literature presents mixed responses regarding GPT's utility and integration in dentistry.
• Further research with extensive methodological rigor is essential before widespread integration into clinical dental workflows.
• Addressing the identified challenges and establishing ethical guidelines are paramount for the successful adoption of GPT in dentistry.