Search research articles
Contact Us
Filters
Showing results (61-70 of 91) with videos related to
Page
of 10
Sort By:
Journal of Electrocardiology
|
November 27, 2022
An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke risk
Sushravya Raghunath, John M Pfeifer, Christopher R Kelsey, et al.
Circulation. Genomic and Precision Medicine
|
October 23, 2019
Prevalence and Electronic Health Record-Based Phenotype of Loss-of-Function Genetic Variants in Arrhythmogenic Right Ventricular Cardiomyopathy-Associated Genes
Eric D Carruth, Wilson Young, Dominik Beer, et al.
Circulation. Genomic and Precision Medicine
|
March 8, 2021
Clinical Findings and Diagnostic Yield of Arrhythmogenic Cardiomyopathy Through Genomic Screening of Pathogenic or Likely Pathogenic Desmosome Gene Variants
Eric D Carruth, Dominik Beer, Amro Alsaid, et al.
Heart Rhythm
|
April 9, 2026
Multi-Center Validation of an Artificial Intelligence-Enabled ECG Model to Predict 1-Year Risk of Atrial Fibrillation or Flutter
John M Pfeifer, Greg Lee, Sushravya Raghunath, et al.
JACC. Heart Failure
|
May 11, 2020
A Machine Learning Approach to Management of Heart Failure Populations
Linyuan Jing, Alvaro E Ulloa Cerna, Christopher W Good, et al.
Radiology. Cardiothoracic Imaging
|
July 5, 2023
StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE
Yu Wang, Changyu Sun, Sona Ghadimi, et al.
Nature Genetics
|
February 18, 2022
Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank
Sean J Jurgens, Seung Hoan Choi, Valerie N Morrill, et al.
Nature Biomedical Engineering
|
February 9, 2021
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality
Alvaro E Ulloa Cerna, Linyuan Jing, Christopher W Good, et al.
Circulation
|
June 17, 2024
Deep Learning for Echo Analysis, Tracking, and Evaluation of Mitral Regurgitation (DELINEATE-MR)
Aaron Long, Christopher M Haggerty, Joshua Finer, et al.
Journal of the American Heart Association
|
October 18, 2024
Promise and Peril of a Genotype-First Approach to Mendelian Cardiovascular Disease
Babken Asatryan, Brittney Murray, Rafik Tadros, et al.
Page
of 10
Search research articles
Search
Showing results (61-70 of 91) with videos related to
Sort By:
Page
of 10
Journal of Electrocardiology
|
November 27, 2022
An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke risk
Sushravya Raghunath, John M Pfeifer, Christopher R Kelsey, et al.
Circulation. Genomic and Precision Medicine
|
October 23, 2019
Prevalence and Electronic Health Record-Based Phenotype of Loss-of-Function Genetic Variants in Arrhythmogenic Right Ventricular Cardiomyopathy-Associated Genes
Eric D Carruth, Wilson Young, Dominik Beer, et al.
Circulation. Genomic and Precision Medicine
|
March 8, 2021
Clinical Findings and Diagnostic Yield of Arrhythmogenic Cardiomyopathy Through Genomic Screening of Pathogenic or Likely Pathogenic Desmosome Gene Variants
Eric D Carruth, Dominik Beer, Amro Alsaid, et al.
Heart Rhythm
|
April 9, 2026
Multi-Center Validation of an Artificial Intelligence-Enabled ECG Model to Predict 1-Year Risk of Atrial Fibrillation or Flutter
John M Pfeifer, Greg Lee, Sushravya Raghunath, et al.
JACC. Heart Failure
|
May 11, 2020
A Machine Learning Approach to Management of Heart Failure Populations
Linyuan Jing, Alvaro E Ulloa Cerna, Christopher W Good, et al.
Radiology. Cardiothoracic Imaging
|
July 5, 2023
StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE
Yu Wang, Changyu Sun, Sona Ghadimi, et al.
Nature Genetics
|
February 18, 2022
Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank
Sean J Jurgens, Seung Hoan Choi, Valerie N Morrill, et al.
Nature Biomedical Engineering
|
February 9, 2021
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality
Alvaro E Ulloa Cerna, Linyuan Jing, Christopher W Good, et al.
Circulation
|
June 17, 2024
Deep Learning for Echo Analysis, Tracking, and Evaluation of Mitral Regurgitation (DELINEATE-MR)
Aaron Long, Christopher M Haggerty, Joshua Finer, et al.
Journal of the American Heart Association
|
October 18, 2024
Promise and Peril of a Genotype-First Approach to Mendelian Cardiovascular Disease
Babken Asatryan, Brittney Murray, Rafik Tadros, et al.
Page
of 10