Application of AI in predicting postoperative infections using routine blood parameters

The application of artificial intelligence in predicting postoperative infections using routine blood parameters is of interest. Hence, a cohort of 120 surgical patients was analyzed and machine learning models were developed using WBC, CRP, NLR and other markers. The Random Forest model achieved the highest predictive performance with an AUC of 0.93. CRP and NLR were identified as the most influential predictors. Thus, we show the integration of AI for early infection detection in surgical care.