Prediction of pulmonary pressure after Glenn shunts by computed tomography–based machine learning models
Abstract
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). This retrospective study included 96 patients with functional single ventricle who underwent a bidirectional Glenn procedure between November 1, 2009, and July, 31, 2017. All patients underwent...
Paper Details
Title
Prediction of pulmonary pressure after Glenn shunts by computed tomography–based machine learning models
Published Date
Nov 8, 2019
Journal
Volume
30
Issue
3
Pages
1369 - 1377
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