This study advances scoliosis diagnostics by integrating trigonometric models with a smartphone app, achieving 89% accuracy. Machine learning enhances pelvic rotation quantification, addressing anatomical variability. Real-time correction recommendations improve clinical outcomes, paving the way for AI-driven, personalized precision medicine in scoliosis care.
Learning Objectives:
Upon completion, participants will be able to calculate pelvic rotation angles using trigonometric models .
Upon completion, participants will be able to apply a smartphone application to generate real-time correction recommendations for scoliosis.
Upon completion, participants will be able to evaluate anatomical variability impacts on pelvic torsion diagnostics using population-based data.
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