Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Sirish Shrestha"'
Publikováno v:
US Cardiology Review, Vol 13, Iss 2, Pp 110-116 (2020)
Machine learning (ML), a subset of artificial intelligence, is showing promising results in cardiology, especially in cardiac imaging. ML algorithms are allowing cardiologists to explore new opportunities and make discoveries not seen with convention
Externí odkaz:
https://doaj.org/article/b003e0b8af6c4629909c2729364cd61a
Publikováno v:
Interventional Cardiology: Reviews, Research, Resources, Vol 16, Iss , Pp - (2021)
Artificial Intelligence (AI) is the simulation of human intelligence in machines so they can perform various actions and execute decision-making. Machine learning (ML), a branch of AI, can analyse information from data and discover novel patterns. AI
Externí odkaz:
https://doaj.org/article/89315a74f0e8448bbe3eb3643ff8a08a
Autor:
Nobuyuki Kagiyama, Sirish Shrestha, Jung Sun Cho, Muhammad Khalil, Yashbir Singh, Abhiram Challa, Grace Casaclang-Verzosa, Partho P. Sengupta
Publikováno v:
EBioMedicine, Vol 54, Iss , Pp - (2020)
Background: Maturation of ultrasound myocardial tissue characterization may have far-reaching implications as a widely available alternative to cardiac magnetic resonance (CMR) for risk stratification in left ventricular (LV) remodeling. Methods: We
Externí odkaz:
https://doaj.org/article/413aa4e50cde4cd8a25ee20b5aee7a6c
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 8, Iss 17 (2019)
Externí odkaz:
https://doaj.org/article/e8d38cbdfd714d1390b6ba0619a35851
Autor:
Partho P. Sengupta, Sirish Shrestha, Nobuyuki Kagiyama, Yasmin Hamirani, Hemant Kulkarni, Naveena Yanamala, Rong Bing, Calvin W.L. Chin, Tania A. Pawade, David Messika-Zeitoun, Lionel Tastet, Mylène Shen, David E. Newby, Marie-Annick Clavel, Phillippe Pibarot, Marc R. Dweck, Éric Larose, Ezequiel Guzzetti, Mathieu Bernier, Jonathan Beaudoin, Marie Arsenault, Nancy Côté, Russell Everett, William S.A. Jenkins, Christophe Tribouilloy, Julien Dreyfus, Tiffany Mathieu, Cedric Renard, Mesut Gun, Laurent Macron, Jacob W. Sechrist, Joan M. Lacomis, Virginia Nguyen, Laura Galian Gay, Hug Cuéllar Calabria, Ioannis Ntalas, Bernard Prendergast, Ronak Rajani, Arturo Evangelista, João L. Cavalcante
Publikováno v:
JACC: Cardiovascular Imaging. 14:1707-1720
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, symptoms and adverse events develop secondarily to valvular obs
Autor:
Bryan Raybuck, Sandeep Banga, Partho P. Sengupta, Sirish Shrestha, Madhavi Kadiyala, James D. Mills, Abhiram Challa, Mina M. Benjamin, Irfan Zeb, Karthik Seetharam, Sudarshan Balla, Yasmin S. Hamirani, Mohammed Osman
Publikováno v:
Journal of Cardiovascular Computed Tomography. 15:348-355
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
Autor:
Yasir Abdul Ghffar, Partho P. Sengupta, Bryan Raybuck, Mohammed Osman, Sirish Shrestha, Mohammed Alkhouli, Faizan Shaukat, Vinay Badhwar, Nobuyuki Kagiyama
Publikováno v:
The American Journal of Cardiology. 136:122-130
Semisupervised machine-learning methods are able to learn from fewer labeled patient data. We illustrate the potential use of a semisupervised automated machine-learning (AutoML) pipeline for phenotyping patients who underwent transcatheter aortic va
Autor:
Theodore P. Abraham, Luigi P. Badano, Thor Edvardsen, John Gorcsan, Nobuyuki Kagiyama, Allan L. Klein, Wojciech Kosmala, Kenya Kusunose, Thomas H. Marwick, Denisa Muraru, Kazuaki Negishi, Dermot Phelan, Zoran B. Popović, Marielle Scherrer-Crosbie, Partho P. Sengupta, Amil Shah, Sirish Shrestha, Paaladinesh Thavendiranathan, James Thomas, Jens-Uwe Voigt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64c7c7fd3ddd7722db0b2b61a05d442e
https://doi.org/10.1016/b978-0-323-75947-2.00004-0
https://doi.org/10.1016/b978-0-323-75947-2.00004-0
Since its inception, strain imaging in echocardiography has demonstrated significant improvement in technology and has established itself as a sensitive biomarker for assessing cardiac function. Recently, many studies began using strain parameters as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ab81e7940b47726b35972826eca78b6
https://doi.org/10.1016/b978-0-323-75947-2.00019-2
https://doi.org/10.1016/b978-0-323-75947-2.00019-2
Autor:
Partho P. Sengupta, Nobuyuki Kagiyama, Christopher Bianco, Sirish Shrestha, Grace Verzosa, Mina M. Benjamin, George Sokos, Marco Caccamo
Publikováno v:
Eur Heart J Cardiovasc Imaging
Aims Lung Doppler signals (LDS) represent the radial movement of small pulmonary blood vessel walls, caused by pulse waves of cardiac origin. We sought to investigate the accuracy and prognostic value of LDS as a predictor of mitral valve early diast