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).Methods: This retrospective study included...

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Publicado en:	European Radiology Vol. 30; no. 3; pp. 1369 - 1378
Autores principales:	Huang, Lei, Li, Jiahua, Huang, Meiping, Zhuang, Jian, Yuan, Haiyun, Jia, Qianjun, Zeng, Dewen, Que, Lifeng, Xi, Yue, Lin, Jijin, Dong, Yuhao
Formato:	diagnostic images research tables/charts Journal Article
Publicado:	Springer Nature 2020
Acceso en línea:	Ver este registro en EBSCOhost