Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives

Area of Science:

• Dental Science
• Computer Science
• Medical Informatics

Background:

• Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are increasingly integrated into dental practice.
• These technologies offer potential advancements across multiple dental subfields, including periodontology, endodontics, orthodontics, restorative dentistry, and oral pathology.

Purpose of the Study:

• To systematically review the current clinical applications of AI in various fields of dentistry.
• To highlight the advances and limitations of integrating AI, ML, and DL in dental care.
• To identify future research directions for AI in dentistry.

Main Methods:

• Systematic review adhering to the Preferred Reporting Items for Systematic Reviews (PRISMA) statement.
• Data collected from research studies published between 2009 and 2022.
• Analysis of 55 papers sourced from Google Scholar, IEEE, PubMed, and Scopus databases.

Main Results:

• AI demonstrates significant potential to enhance dental care delivery.
• Applications include improved disease diagnosis, prognosis prediction, and personalized treatment planning.
• AI tools can also aid in more accurate dental risk assessment.

Conclusions:

• AI integration in dentistry shows promising results for improving patient outcomes and clinical efficiency.
• Identified limitations in current studies necessitate further research and development.
• Future directions should focus on refining AI algorithms and validating their clinical efficacy.