Detalhe da pesquisa
1.
rECHOmmend: An ECG-Based Machine Learning Approach for Identifying Patients at Increased Risk of Undiagnosed Structural Heart Disease Detectable by Echocardiography.
Circulation
; 146(1): 36-47, 2022 07 05.
Artigo
Inglês
| MEDLINE | ID: mdl-35533093
2.
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.
J Electrocardiol
; 76: 61-65, 2023.
Artigo
Inglês
| MEDLINE | ID: mdl-36436476
3.
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.
Circulation
; 143(13): 1287-1298, 2021 03 30.
Artigo
Inglês
| MEDLINE | ID: mdl-33588584
4.
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality.
Nat Biomed Eng
; 5(6): 546-554, 2021 06.
Artigo
Inglês
| MEDLINE | ID: mdl-33558735
5.
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network.
Nat Med
; 26(6): 886-891, 2020 06.
Artigo
Inglês
| MEDLINE | ID: mdl-32393799
6.
A Machine Learning Approach to Management of Heart Failure Populations.
JACC Heart Fail
; 8(7): 578-587, 2020 07.
Artigo
Inglês
| MEDLINE | ID: mdl-32387064