Partho P. Sengupta
Artificial Intelligence · 2008–2019
A researcher in the Science corpus: 11 papers; trusts 2 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 15 citations into it
- Health Informatics — 6 citations into it
Whom Partho P. Sengupta trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- William Stafford Noble (in Statistical Learning Theory)
- Nils J. Nilsson (in Artificial Intelligence)
Who trusts Partho P. Sengupta
- Sameer Quazi (in Cardiology and Cardiovascular Medicine)
Papers from Partho P. Sengupta's perspective
Ordered by how strongly the researchers Partho P. Sengupta trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- The WEKA data mining software: an update
- The Nature of Statistical Learning Theory, Second Edition (Statistics for Engineering and Information Science)
- Two-dimensional strain-a novel software for real-time quantitative echocardiographic assessment of myocardial function. (Journal of the American Society of Echocardiography)
- Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review
- Neural Networks: A Comprehensive Foundation
- Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features (IEEE Transactions on Medical Imaging)
- Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal (Artif. Intell. Medicine)
- Forecasting the Impact of Heart Failure in the United States (Circulation: Heart Failure)
- Support vector machine
Their papers
- Artificial Intelligence in Cardiovascular Imaging (2019) — 546 citations
- Standardization of left atrial, right ventricular, and right atrial deformation imaging using two-dimensional speckle tracking echocardiography: a consensus document of the EACVI/ASE/Industry Task Force to standardize deformation imaging (2018) — 1,459 citations
- Machine learning in cardiovascular medicine: are we there yet? (2018) — 457 citations
- Mobile technology and the digitization of healthcare. (2016) — 407 citations
- Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography. (2016) — 368 citations
- Definitions for a common standard for 2D speckle tracking echocardiography: consensus document of the EACVI/ASE/Industry Task Force to standardize deformation imaging. (2015) — 746 citations
- Definitions for a common standard for 2D speckle tracking echocardiography: consensus document of the EACVI/ASE/Industry Task Force to standardize deformation imaging. (2015) — 1,395 citations
- Current and evolving echocardiographic techniques for the quantitative evaluation of cardiac mechanics: ASE/EAE consensus statement on methodology and indications endorsed by the Japanese Society of Echocardiography. (2011) — 1,373 citations
- Current and evolving echocardiographic techniques for the quantitative evaluation of cardiac mechanics: ASE/EAE consensus statement on methodology and indications endorsed by the Japanese Society of Echocardiography. (2011) — 992 citations
- Assessment of myocardial mechanics using speckle tracking echocardiography: fundamentals and clinical applications. (2010) — 1,111 citations
- Twist mechanics of the left ventricle: principles and application. (2008) — 618 citations