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<p>Synthetic data generation across domains can bridge gaps between visual training, skill development, and personalized surgical planning, ultimately transforming how surgeons and artificial intelligence (AI) systems prepare for the complexities of the operating room. In this Perspective, we explore applications of synthetic data to advance surgical education and AI across three key areas: visual data synthesis for training surgeons and AI systems, surgical simulation for skill development and robotics, and digital twins for patient-specific surgical planning and guidance. These domains have largely remained siloed, but their integration has the potential to transform surgical training and AI development across the entire surgical workflow. To fully realize this potential, synthetic data must extend beyond routine surgical events to model atypical anatomy and intraoperative complications-the high-stakes clinical scenarios where enhanced training and AI support are most critical.</p>

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Empowering surgeons with integrated synthetic data: solutions for mastering complex clinical scenarios

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月30日

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  • Yann Sakref,
  • Lalithkumar Seenivasan,
  • Hao Ding,
  • Ruhika Iyer,
  • Danush Kumar Venkatesh,
  • Stefanie Speidel,
  • Mathias Unberath,
  • Jeffrey K. Jopling,
  • Lisa Marie Knowlton

摘要

Synthetic data generation across domains can bridge gaps between visual training, skill development, and personalized surgical planning, ultimately transforming how surgeons and artificial intelligence (AI) systems prepare for the complexities of the operating room. In this Perspective, we explore applications of synthetic data to advance surgical education and AI across three key areas: visual data synthesis for training surgeons and AI systems, surgical simulation for skill development and robotics, and digital twins for patient-specific surgical planning and guidance. These domains have largely remained siloed, but their integration has the potential to transform surgical training and AI development across the entire surgical workflow. To fully realize this potential, synthetic data must extend beyond routine surgical events to model atypical anatomy and intraoperative complications-the high-stakes clinical scenarios where enhanced training and AI support are most critical.