Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Zachi I Attia"'
Autor:
Bruno Oliveira de Figueiredo Brito, Zachi I Attia, Larissa Natany A Martins, Pablo Perel, Maria Carmo P Nunes, Ester Cerdeira Sabino, Clareci Silva Cardoso, Ariela Mota Ferreira, Paulo R Gomes, Antonio Luiz Pinho Ribeiro, Francisco Lopez-Jimenez
Publikováno v:
PLoS Neglected Tropical Diseases, Vol 15, Iss 12, p e0009974 (2021)
BackgroundLeft ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm show
Externí odkaz:
https://doaj.org/article/4a9e105afca0448e9ce7623766076c1f
Autor:
Zachi I Attia, Alan Sugrue, Samuel J Asirvatham, Michael J Ackerman, Suraj Kapa, Paul A Friedman, Peter A Noseworthy
Publikováno v:
PLoS ONE, Vol 13, Iss 8, p e0201059 (2018)
BACKGROUND:Dofetilide is an effective antiarrhythmic medication for rhythm control in atrial fibrillation, but carries a significant risk of pro-arrhythmia and requires meticulous dosing and monitoring. The cornerstone of this monitoring, measurement
Externí odkaz:
https://doaj.org/article/70d01669886244acb9a6933f22a0c14b
Autor:
Eunjung Lee, Saki Ito, William R. Miranda, Francisco Lopez-Jimenez, Garvan C. Kane, Samuel J. Asirvatham, Peter A. Noseworthy, Paul A. Friedman, Rickey E. Carter, Barry A. Borlaug, Zachi I. Attia, Jae K. Oh
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-7 (2024)
Abstract Assessment of left ventricular diastolic function plays a major role in the diagnosis and prognosis of cardiac diseases, including heart failure with preserved ejection fraction. We aimed to develop an artificial intelligence (AI)-enabled el
Externí odkaz:
https://doaj.org/article/8a74fb9cbbf3475598191b5f7af8ade7
Autor:
Demilade Adedinsewo, MD, Jennifer Dugan, BA, Patrick W. Johnson, MS, Erika J. Douglass, DrPH, Andrea Carolina Morales-Lara, MD, Mark A. Parkulo, MD, Henry H. Ting, MD, Leslie T. Cooper, MD, Luis R. Scott, MD, Arturo M. Valverde, MD, Deepak Padmanabhan, MBBS, Nicholas S. Peters, MD, Patrik Bachtiger, MBBS, Mihir Kelshiker, MBBS, Francisco Fernandez-Aviles, MD, Felipe Atienza, MD, Taya V. Glotzer, MD, Marc K. Lahiri, MD, Paari Dominic, MD, Zachi I. Attia, PhD, Suraj Kapa, MD, Peter A. Noseworthy, MD, Naveen L. Pereira, MD, Jessica Cruz, MBA, Elie F. Berbari, MD, Rickey E. Carter, PhD, Paul A. Friedman, MD
Publikováno v:
Mayo Clinic Proceedings: Digital Health, Vol 1, Iss 4, Pp 455-466 (2023)
Objective: To evaluate the ability of a neural network to identify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using point-of-care electrocardiography obtained with a portable device. Patient and Methods: We enrolled 2827 p
Externí odkaz:
https://doaj.org/article/70df8238488d417d98aee85d5f6a403d
Autor:
Yoshihisa Kanaji, Ilke Ozcan, David N. Tryon, Ali Ahmad, Jaskanwal Deep Singh Sara, Brad Lewis, Paul Friedman, Peter A Noseworthy, Lilach O. Lerman, Tsunekazu Kakuta, Zachi I. Attia, Amir Lerman
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 13, Iss 5 (2024)
Background Recent studies have indicated high rates of future major adverse cardiovascular events in patients with Takotsubo cardiomyopathy (TC), but there is no well‐established tool for risk stratification. This study sought to evaluate the progn
Externí odkaz:
https://doaj.org/article/a13d5bfe05e248e3b6aba2b5460aa727
Autor:
Samir Awasthi, Nikhil Sachdeva, Yash Gupta, Ausath G. Anto, Shahir Asfahan, Ruben Abbou, Sairam Bade, Sanyam Sood, Lars Hegstrom, Nirupama Vellanki, Heather M. Alger, Melwin Babu, Jose R. Medina-Inojosa, Robert B. McCully, Amir Lerman, Mark Stampehl, Rakesh Barve, Zachi I. Attia, Paul A. Friedman, Venky Soundararajan, Francisco Lopez-Jimenez
Publikováno v:
EClinicalMedicine, Vol 65, Iss , Pp 102259- (2023)
Summary: Background: Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death worldwide, driven primarily by coronary artery disease (CAD). ASCVD risk estimators such as the pooled cohort equations (PCE) facilitate risk stratifica
Externí odkaz:
https://doaj.org/article/97d6bc637a9f484f91ae2a92cbf0ea4a
Autor:
Julian Libiseller-Egger, Jody E. Phelan, Zachi I. Attia, Ernest Diez Benavente, Susana Campino, Paul A. Friedman, Francisco Lopez-Jimenez, David A. Leon, Taane G. Clark
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has s
Externí odkaz:
https://doaj.org/article/379ddc9b3fe843058aa78cf23f1306e2
Autor:
Maren Maanja, MD, PhD, Peter A. Noseworthy, MD, FHRS, Jeffrey B. Geske, MD, Michael J. Ackerman, MD, PhD, Adelaide M. Arruda-Olson, MD, PhD, Steve R. Ommen, MD, Zachi I. Attia, PhD, Paul A. Friedman, MD, FHRS, Konstantinos C. Siontis, MD, FHRS
Publikováno v:
Cardiovascular Digital Health Journal, Vol 3, Iss 6, Pp 289-296 (2022)
Background: An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM). However, its application in routine clinical practice may be challenging owing to the low d
Externí odkaz:
https://doaj.org/article/d6a32c2b206d4643bfa0e0bbcbb3a8d4
Autor:
David M. Harmon, Demilade Adedinsewo, Jeremy R. Van't Hof, Matthew Johnson, Sharonne N. Hayes, Francisco Lopez-Jimenez, Clarence Jones, Zachi I. Attia, Paul A. Friedman, Christi A. Patten, Lisa A. Cooper, LaPrincess C. Brewer
Publikováno v:
American Journal of Preventive Cardiology, Vol 12, Iss , Pp 100431- (2022)
Objective: With the emergence of artificial intelligence (AI)-based health interventions, systemic racism remains a concern as these advancements are frequently developed without race-specific data analysis or validation. To evaluate the potential ut
Externí odkaz:
https://doaj.org/article/6397e9f918784c22b13e6ecc5f33380b
Autor:
Anthony H. Kashou, MD, Siva K. Mulpuru, MD, FHRS, Abhishek J. Deshmukh, MBBS, FHRS, Wei-Yin Ko, MS, Zachi I. Attia, PhD, Rickey E. Carter, PhD, Paul A. Friedman, MD, FHRS, Peter A. Noseworthy, MD, FHRS
Publikováno v:
Cardiovascular Digital Health Journal, Vol 2, Iss 3, Pp 164-170 (2021)
Objective: To develop an artificial intelligence (AI)–enabled electrocardiogram (ECG) algorithm capable of comprehensive, human-like ECG interpretation and compare its diagnostic performance against conventional ECG interpretation methods. Methods:
Externí odkaz:
https://doaj.org/article/6b4f9f1bbee544b19a1347a8a74767e1