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Artificial intelligence (AI) is transforming medicine, with machine learning and deep learning enhancing surgical planning and intraoperative support. Challenges remain in AI implementation, data governance, and ethical considerations for surgical applications.

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Area of Science:

  • Medicine
  • Computer Science
  • Surgical Technology

Background:

  • Artificial intelligence (AI) is gaining significant traction in medicine.
  • AI encompasses machine learning, deep learning, natural language processing, computer vision, and generative modeling.
  • These AI components have emerging applications within surgery.

Purpose of the Study:

  • To review foundational AI components.
  • To examine emerging AI applications in surgery (preoperative, intraoperative).
  • To discuss challenges and future directions of AI in surgical workflows.

Main Methods:

  • Literature review of AI foundational components.
  • Analysis of AI applications in surgical domains.
  • Discussion of AI implementation challenges in surgery.

Main Results:

  • AI enhances preoperative surgical planning through risk stratification and automated imaging analysis (segmentation, 3D reconstruction).
  • Intraoperative AI improves safety, efficiency, and challenge recognition via phase recognition, anatomic identification, AR overlay, and decision support.
  • AI in robotic surgery is advancing, though fully autonomous systems are distant.

Conclusions:

  • AI offers transformative potential in surgery, from planning to intraoperative assistance.
  • Significant challenges persist, including data governance, transparency, regulation, generalizability, and ethical concerns.
  • Continued research and development are crucial for robust AI integration into surgical practice.