Partho P. Sengupta
West Virginia University
Internal medicineRadiologySurgeryArtificial intelligenceCardiologyHemodynamicsCardiac imagingHeart failureSpeckle tracking echocardiographyVentricleStenosisValve replacementDiastolic functionIn patientTranscatheter aorticMyocardial infarctionDiastoleMedicineEjection fractionCardiac cycle
Publications 380
#1Sandeep Banga (WVU: West Virginia University)H-Index: 4
#1Sandeep Banga (WVU: West Virginia University)H-Index: 1
Last. Yasmin S. Hamirani (WVU: West Virginia University)
view all 13 authors...
Abstract Background Transesophageal echocardiography (TEE) is the standard imaging modality used to assess the left atrial appendage (LAA) after transcatheter device occlusion. Cardiac computed tomography angiography (CCTA) offers an alternative non-invasive modality in these patients. We aimed to conduct a comparison of the two modalities. Methods We performed a comprehensive systematic review of the current literature pertaining to CCTA to establish its usefulness during follow-up for patients...
#1E. Potter (Baker IDI Heart and Diabetes Institute)H-Index: 5
#2Carlos H M Rodrigues (Baker IDI Heart and Diabetes Institute)H-Index: 1
Last. Thomas H. Marwick (Monash University)H-Index: 137
view all 6 authors...
Abstract Objectives To identify whether machine learning from processing of continuous wave transforms (CWTs) to provide an “energy waveform” electrocardiogram (ewECG) could be integrated with echo...
#1Ambarish Pandey (UTSW: University of Texas Southwestern Medical Center)H-Index: 40
#2Nobuyuki Kagiyama (WVU: West Virginia University)H-Index: 14
Last. Partho P. Sengupta (WVU: West Virginia University)H-Index: 58
view all 7 authors...
Abstract Objectives The authors explored a deep neural network (DeepNN) model that integrates multidimensional echocardiographic data to identify distinct patient subgroups with heart failure with ...
#1Partho P. Sengupta (WVU: West Virginia University)H-Index: 58
Last. João L. CavalcanteH-Index: 27
view all 39 authors...
Abstract Objectives The authors explored the development and validation of machine-learning models for augmenting the echocardiographic grading of aortic stenosis (AS) severity. Background In AS, s...
1 CitationsSource