AI-driven perioperative risk stratification and complication management in craniomaxillofacial surgery: current progress and future directions - Summary - MDSpire
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Advancements in AI for Perioperative Risk Assessment and Complication Management in Craniomaxillofacial Surgery: Current Insights and Future Perspectives

  • By

  • HaiLian Chen

  • Shuang Zou

  • Linlin Zheng

  • July 6, 2026

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Objective:

To summarize recent advances in AI applications for perioperative risk stratification and complication management in craniomaxillofacial surgery.

Approach:
  • Preoperative Management: Focus on intelligent early recognition of syndromic craniosynostosis to improve individualized treatment protocols.
  • Intraoperative Support: AI provides decision support and safety monitoring during surgical procedures.
  • Postoperative Management: AI aids in risk stratification and quantification of outcomes after surgery.
Key Findings:
  • AI enhances diagnostic accuracy and risk stratification in craniomaxillofacial surgery.
  • Current research faces challenges in model interpretability, external validation, and clinical integration.
  • Future directions include multimodal AI, explainable AI, and generative AI for personalized perioperative management.
Interpretation:

Limitations:
  • Challenges in data quality and generalizability.
  • Issues with model interpretability and clinical trust.
  • Barriers to clinical translation and implementation.
Conclusion:

The review serves as a structured reference for the intelligent development of perioperative care in craniomaxillofacial surgery.

Original Source(s)

AI-driven perioperative risk stratification and complication management in craniomaxillofacial surgery: current progress and future directions

  • by HaiLian Chen, Shuang Zou, Linlin Zheng

  • July 6, 2026

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