Machine Learning-Based Prediction of Post-PKP Frailty: A Retrospective Cohort Study

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Retrospective cohort analysis predicts frailty outcomes after PKP, highlighting osteoporosis factors.

Machine learning models accurately predict post-PKP frailty, suggesting preventive strategies.
The Extreme Gradient Boost model achieved an AUC of 0.950, indicating high predictive accuracy.
Retrospective cohort study analyzed 4599 PKP patients, focusing on key predictors like residual LBP.
Optimizing ML models may mitigate frailty risks, highlighting the need for standardized osteoporosis therapy.

Xu et al. (2025) studied this question.

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