Applications of artificial intelligence in tooth extraction: A systematic review

Area of Science:

• Dental Surgery
• Artificial Intelligence in Medicine
• Oral Health Technology

Background:

• Tooth extraction is a prevalent dental procedure.
• Advancements in artificial intelligence (AI) are driving new research in dental applications.
• The integration of AI in tooth extraction is an emerging field of study.

Purpose of the Study:

• To review the current literature on the applicability of AI in tooth extraction.
• To identify key research areas and trends in AI-assisted tooth extraction.
• To assess the potential impact of AI on dental decision-making and treatment strategies.

Main Methods:

• A systematic literature search was conducted in June 2024.
• Databases searched included PubMed, Scopus, and Web of Science.
• Search terms combined 'tooth extraction' with 'artificial intelligence', 'machine learning', or 'deep learning'.

Main Results:

• Thirty-five articles met the eligibility criteria for the review.
• Dominant topics included the relationship between tooth roots and the inferior alveolar nerve (10 articles) and tooth extraction decision-making (8 articles).
• Other areas covered were extraction difficulty, maxillary sinus evaluation, predictive models for jaw osteonecrosis/osteomyelitis, post-extraction complications, and ChatGPT applications.

Conclusions:

• AI research in tooth extraction is diverse, reflecting the complexity of dental care.
• Findings can enhance clinical decision-making, treatment planning, and preventive measures.
• The study underscores the need for further research to fully leverage AI in dentistry.