AIMC Topic: Univentricular Heart

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

European radiology Nov 8, 2019
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 tomograph...
Humans Machine Learning Algorithms Prognosis Retrospective Studies Tomography, X-Ray Computed Female Young Adult Male Infant Lung Adolescent Child, Preschool Child Logistic Models Support Vector Machine Blood Pressure Bayes Theorem Discriminant Analysis Double Outlet Right Ventricle Fontan Procedure Heart Defects, Congenital Pulmonary Atresia Tricuspid Atresia Cardiac Catheterization Transposition of Great Vessels Pulmonary Artery Heart Septal Defects Univentricular Heart
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A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.

Radiology. Artificial intelligence Jan 1, 2024
Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation of cardiac MRI data from a multicenter registry of patients with Fontan circulation (Fontan Outcomes Registry Using CMR Examinations [FORCE]). Materia...
Humans Retrospective Studies Adult Deep Learning Child Magnetic Resonance Imaging Multicenter Studies as Topic Heart Heart Ventricles Univentricular Heart
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