Enhancing post-induction hypotension prediction based on exemplar learning with crossover restart strategy driven feature selection.

The bECRIME-SVM model provides a valuable tool for the clinical prediction of PIH, with high accuracy and specificity. Identifying significant predictive features offers essential insights for the early detection and management of PIH, ultimately contributing to improved postoperative outcomes for patients undergoing general anesthesia.