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Updated: Jul 30, 2025

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement
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Artificial Intelligence and Machine Learning Applications in Spine Surgery.

Nathan J Lee1, Joseph M Lombardi2, Ronald A Lehman2

  • 1Department of Orthopaedics, Columbia University Medical Center, The Och Spine Hospital at New York-Presbyterian, New York, NY, USA njl2116@cumc.columbia.edu.

International Journal of Spine Surgery
|May 16, 2023
PubMed
Summary
This summary is machine-generated.

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Artificial intelligence and machine learning offer advanced predictive models for spine surgery, improving patient outcomes and reducing complications. These tools enhance preoperative optimization and risk stratification in complex spinal procedures.

Area of Science:

  • Spine surgery
  • Artificial intelligence
  • Machine learning
  • Predictive modeling

Background:

  • Spine pathology presents complex patient cases with high complication rates.
  • Traditional statistical methods have limitations in predictive accuracy and variable consideration.
  • There is a need for advanced analytical approaches in spine surgery.

Purpose of the Study:

  • To review current machine learning applications in spine surgery.
  • To discuss the use of AI and ML in preoperative optimization.
  • To explore risk stratification and predictive modeling for spinal conditions.

Main Methods:

  • Literature review of published machine learning applications in spine surgery.
  • Analysis of studies focusing on cervical, lumbar, and adult spinal deformity.
Keywords:
adult spinal deformityartificial intelligencecervical spinelumbar spinemachine learningpredictive model

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  • Synthesis of findings on AI/ML for patient-centered predictive models.

    • Main Results:

    • Machine learning shows promise in enhancing predictive accuracy for spine surgery outcomes.
    • AI and ML applications are emerging for preoperative optimization and risk stratification.
    • These technologies can potentially lead to more personalized patient care.

    Conclusions:

    • Machine learning is a powerful tool for developing accurate predictive models in spine surgery.
    • AI and ML can significantly contribute to optimizing patient care and reducing complications.
    • Further research into ML applications is crucial for advancing spine surgery practices.