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Machine Learning in Spine Surgery: A Narrative Review
Samuel Adida1, Andrew D Legarreta1, Joseph S Hudson1
1Department of Neurosurgery, University of Pittsburgh School of Medicine, Pittsburgh , Pennsylvania , USA.
Artificial intelligence (AI) and machine learning (ML) are revolutionizing spine surgery with improved decision-making and outcomes. This review explores AI applications across preoperative, intraoperative, and postoperative phases, highlighting future directions.
Area of Science:
- Neurosurgery
- Medical Imaging
- Artificial Intelligence
Background:
- Artificial intelligence (AI) and machine learning (ML) present transformative potential in spine surgery.
- Recent advancements have seen ML applications in surgical decision-making, intraoperative guidance, and outcome optimization.
- ML offers solutions for diverse clinical needs, enhancing diagnostic and surgical methodologies.
Conclusions:
- Machine learning holds significant promise for advancing spine surgery by improving efficiency and patient outcomes.
- Addressing ethical concerns and technical challenges is crucial for widespread adoption.
- Future research should focus on augmented and mixed reality integration, alongside mitigating bias and ensuring generalizability.
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