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European Heart Journal
|
August 7, 2019
Routinely reported ejection fraction and mortality in clinical practice: where does the nadir of risk lie?
Gregory J Wehner, Linyuan Jing, Christopher M Haggerty, et al.
Circulation. Genomic and Precision Medicine
|
August 31, 2021
Predictive Accuracy of a Clinical and Genetic Risk Model for Atrial Fibrillation
Shaan Khurshid, Nina Mars, Christopher M Haggerty, et al.
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. Arrhythmia and Electrophysiology
|
May 13, 2018
Functional Invalidation of Putative Sudden Infant Death Syndrome-Associated Variants in the <i>KCNH2</i>-Encoded Kv11.1 Channel
Jennifer L Smith, David J Tester, Allison R Hall, 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.
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.
American Journal of Obstetrics and Gynecology
|
April 15, 2020
A genome-wide association study of polycystic ovary syndrome identified from electronic health records
Yanfei Zhang, Kevin Ho, Jacob M Keaton, et al.
Nature Medicine
|
May 13, 2020
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
Sushravya Raghunath, Alvaro E Ulloa Cerna, Linyuan Jing, et al.
Circulation
|
February 16, 2021
Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation-Related Stroke
Sushravya Raghunath, John M Pfeifer, Alvaro E Ulloa-Cerna, et al.
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Search research articles
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Showing results (11-20 of 26) with videos related to
Sort By:
Page
of 3
European Heart Journal
|
August 7, 2019
Routinely reported ejection fraction and mortality in clinical practice: where does the nadir of risk lie?
Gregory J Wehner, Linyuan Jing, Christopher M Haggerty, et al.
Circulation. Genomic and Precision Medicine
|
August 31, 2021
Predictive Accuracy of a Clinical and Genetic Risk Model for Atrial Fibrillation
Shaan Khurshid, Nina Mars, Christopher M Haggerty, et al.
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. Arrhythmia and Electrophysiology
|
May 13, 2018
Functional Invalidation of Putative Sudden Infant Death Syndrome-Associated Variants in the <i>KCNH2</i>-Encoded Kv11.1 Channel
Jennifer L Smith, David J Tester, Allison R Hall, 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.
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.
American Journal of Obstetrics and Gynecology
|
April 15, 2020
A genome-wide association study of polycystic ovary syndrome identified from electronic health records
Yanfei Zhang, Kevin Ho, Jacob M Keaton, et al.
Nature Medicine
|
May 13, 2020
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
Sushravya Raghunath, Alvaro E Ulloa Cerna, Linyuan Jing, et al.
Circulation
|
February 16, 2021
Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation-Related Stroke
Sushravya Raghunath, John M Pfeifer, Alvaro E Ulloa-Cerna, et al.
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of 3