Advancements in Dental Science through Artificial Intelligence and Machine Learning: A Comprehensive Review

Area of Science:

• Dentistry
• Artificial Intelligence
• Machine Learning

Background:

• Artificial intelligence (AI) and machine learning (ML) offer transformative potential in dentistry.
• Understanding the applications of supervised, unsupervised, and reinforcement learning (RL) is key to advancing oral healthcare.

Purpose of the Study:

• To review the applications of AI and ML in dentistry across supervised, unsupervised, and RL paradigms.
• To highlight significant developments and real-world applications of AI and ML in dental practice.

Main Methods:

• Narrative review of AI and ML applications in dentistry.
• Examination of supervised learning for disease diagnosis (caries, periodontal conditions, oral cancers).
• Analysis of unsupervised learning for pattern discovery in patient data and resource allocation.
• Evaluation of RL techniques for adaptive and personalized treatment strategies.

Main Results:

• Supervised learning demonstrates high accuracy in diagnosing dental diseases.
• Unsupervised learning uncovers hidden patterns for improved preventive care.
• RL supports personalized treatment by optimizing decisions based on patient feedback.
• AI-driven tools are emerging for imaging, behavior encouragement, and treatment.

Conclusions:

• AI and ML are significantly advancing dental science and patient care.
• Interdisciplinary collaboration and further research are crucial to overcome challenges and realize AI's full potential in dentistry.
• Adoption of these technologies can lead to a more patient-centered, data-driven, and efficient oral healthcare model.