New model predicts risk of intestinal resection in hernia patients

Advanced machine-learning techniques successfully identified key predictors of intestinal resection in incarcerated inguinal hernia patients, including peritonitis, intestinal obstruction, neutrophil count, C-reactive protein, and preoperative total protein. The constructed model, validated externally, demonstrated strong predictive performance with an area under the curve exceeding 0.8 for all ten algorithms tested. Notably, the k-nearest neighbor algorithm showed the highest performance. This model aids clinicians in accurately assessing surgical risks and intestinal viability.