Predicting postoperative transfusion in elective total HIP and knee arthroplasty: Comparison of different machine learning models of a case-control study

Abstract

The risk factors identified in the current study can provide specific, personalized postoperative transfusion risk assessment for a patient considering lower limb TJA. Furthermore, the predictive accuracies of LSTM and RF algorithms were significantly higher than the others, making them potential tools for future personalized preoperative prediction of risk for postoperative transfusion.