Artificial Intelligence-Based Assessment of Left Ventricular Filling Pressures From 2-Dimensional Cardiac Ultrasound Images | Zendy

Alaa Mabrouk Salem Omar | Zendy; Khader Shameer | Zendy; Sukrit Narula | Zendy; Mohamed Ahmed Abdel Rahman | Zendy; Osama Rifaie | Zendy; Jagat Narula | Zendy; Joel T. Dudley | Zendy; Partho P. Sengupta | Zendy

Open Access

Artificial Intelligence-Based Assessment of Left Ventricular Filling Pressures From 2-Dimensional Cardiac Ultrasound Images

Author(s) -

Alaa Mabrouk Salem Omar,

Khader Shameer,

Sukrit Narula,

Mohamed Ahmed Abdel Rahman,

Osama Rifaie,

Jagat Narula,

Joel T. Dudley,

Partho P. Sengupta

Publication year - 2017

Publication title -

jacc. cardiovascular imaging

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 5.79

H-Index - 120

eISSN - 1936-878X

pISSN - 1876-7591

DOI - 10.1016/j.jcmg.2017.05.003

Subject(s) - ventricular filling , cardiology , medicine , diastole , ultrasound , speckle pattern , speckle tracking echocardiography , blood pressure , radiology , artificial intelligence , heart failure , computer science , ejection fraction

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

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