Publications by authors named "Erik Stenqvist"
Acad Radiol
December 2024
Article Synopsis
- The study focuses on developing a machine-learning model to predict anastomotic leakage (AL) after esophagectomy for esophageal cancer, as this complication poses significant risks post-surgery.
- 471 patients' preoperative CT and clinical data were analyzed to create and test the model using an XGBoost algorithm, with performance metrics measured using ROC curves.
- The model showed a noteworthy accuracy, achieving a 79.2% area under the curve, which can aid in identifying patients at risk of AL, particularly where clinical indicators suggest low probability.*
