当前位置：
X-MOL 学术
›
JACC Cardiovasc. Imaging
›
论文详情
Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
Artificial Intelligence-Based Assessment of Left Ventricular Filling Pressures From 2-Dimensional Cardiac Ultrasound Images
JACC: Cardiovascular Imaging ( IF 12.8 ) Pub Date : 2018-03-01 , DOI: 10.1016/j.jcmg.2017.05.003 Alaa Mabrouk Salem Omar , Khader Shameer , Sukrit Narula , Mohamed Ahmed Abdel Rahman , Osama Rifaie , Jagat Narula , Joel T. Dudley , Partho P. Sengupta
JACC: Cardiovascular Imaging ( IF 12.8 ) Pub Date : 2018-03-01 , DOI: 10.1016/j.jcmg.2017.05.003 Alaa Mabrouk Salem Omar , Khader Shameer , Sukrit Narula , Mohamed Ahmed Abdel Rahman , Osama Rifaie , Jagat Narula , Joel T. Dudley , Partho P. Sengupta
The estimation of left ventricular (LV) filling pressure from the ratio of transmitral and annular velocities (E/e′) is used commonly for identifying diastolic dysfunction in patients who complain of exertional dyspnea [(1)][1]. We have recently illustrated that LV and left atrial speckle tracking
中文翻译：
通常根据传递速度与环形速度之比（E / e'）估算左心室充盈压，以鉴定抱怨劳力性呼吸困难的患者的舒张功能障碍[（1）] [1]。我们最近已经说明左心房和左心房斑纹追踪
更新日期：2018-03-06
中文翻译：
基于人工智能的二维心脏超声图像左心室充盈压评估
通常根据传递速度与环形速度之比（E / e'）估算左心室充盈压，以鉴定抱怨劳力性呼吸困难的患者的舒张功能障碍[（1）] [1]。我们最近已经说明左心房和左心房斑纹追踪
京公网安备 11010802027423号