Prediction of pulmonary pressure after Glenn shunts by computed tomography–based machine learning models

Objectives This study aimed to develop non-invasive machine learning classifiers for predicting post–Glenn shunt patients with low and high risks of a mean pulmonary arterial pressure (mPAP) > 15 mmHg based on preoperative cardiac computed tomography (CT).