Objective <p>This narrative review aims to explore the current applications and future prospects of AI within the subfields of oral and maxillofacial surgery (OMS), emphasizing its potential benefits and anticipated challenges.</p> Methods <p>A detailed review of the literature was conducted to evaluate the role of AI in oral and maxillofacial surgery. All domains within OMS were reviewed with a focus on diagnostic, therapeutic and prognostic interventions.</p> Results <p>AI has been successfully integrated into surgical specialties to enhance clinical outcomes. In OMS, AI demonstrates potential to improve clinical and administrative workflows in both ambulatory and hospital-based settings. Notable applications include more accurate risk prediction, minimally invasive surgical techniques, and optimized postoperative management.</p> Conclusion <p>OMS stands to benefit enormously from the integration of AI. However, significant roadblocks, such as ethical concerns, data security, and integration challenges, must be addressed to ensure effective adoption. Further research and innovation are needed to fully realize the potential of AI in this specialty. </p>

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The current landscape of artificial intelligence in oral and maxillofacial surgery– a narrative review

  • Rushil Rajiv Dang,
  • Balram Kadaikal,
  • Sam El Abbadi,
  • Branden R. Brar,
  • Amit Sethi,
  • Radhika Chigurupati

摘要

Objective

This narrative review aims to explore the current applications and future prospects of AI within the subfields of oral and maxillofacial surgery (OMS), emphasizing its potential benefits and anticipated challenges.

Methods

A detailed review of the literature was conducted to evaluate the role of AI in oral and maxillofacial surgery. All domains within OMS were reviewed with a focus on diagnostic, therapeutic and prognostic interventions.

Results

AI has been successfully integrated into surgical specialties to enhance clinical outcomes. In OMS, AI demonstrates potential to improve clinical and administrative workflows in both ambulatory and hospital-based settings. Notable applications include more accurate risk prediction, minimally invasive surgical techniques, and optimized postoperative management.

Conclusion

OMS stands to benefit enormously from the integration of AI. However, significant roadblocks, such as ethical concerns, data security, and integration challenges, must be addressed to ensure effective adoption. Further research and innovation are needed to fully realize the potential of AI in this specialty.