A Machine Learning-Based Clinical Decision Support Tool for Intertrochanteric Hip Fracture Patients to Predict Postoperative Anemia Risk: A Retrospective Cohort Study.

Eight variables were selected to build seven machine learning models.

Among these, the SVM model exhibited the best predictive performance in terms of discrimination, calibration, and clinical applicability, with an AUC range of 0.827-0.831.