Optimizing incision placement for maximum disc and endplate preparation in lumbar endo-fusion using parametric modeling, genetic algorithms, and machine learning

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Uniportal spinal endoscopy has evolved to facilitate lumbar fusion surgery, utilizing larger instruments through a wider working canal.
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The incision placement in endoscopic surgery is crucial for maximizing disc and endplate preparation, impacting fusion success.
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Achieving over 30% endplate and disc preparation is essential for improved structural stability and fusion rates in lumbar surgeries.
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This study employs parametric modeling and genetic algorithms to optimize incision placement for enhanced surgical outcomes.
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Machine learning models predict optimal incision sites based on patient-specific anatomical parameters from preoperative MRI scans.

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