nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
A comprehensive artificial intelligence–enabled electrocardiogram interpretation program
|
Kashou, Anthony H. |
|
|
|
2 |
p. 62-70 |
artikel |
2 |
Advancing telemedicine in cardiology: A comprehensive review of evolving practices and outcomes in a postpandemic context
|
Huerne, Katherine |
|
|
|
2 |
p. 96-110 |
artikel |
3 |
Artificial intelligence–enabled classification of hypertrophic heart diseases using electrocardiograms
|
Haimovich, Julian S. |
|
|
|
2 |
p. 48-59 |
artikel |
4 |
Artificial intelligence–enabled electrocardiogram to distinguish atrioventricular re-entrant tachycardia from atrioventricular nodal re-entrant tachycardia
|
Sau, Arunashis |
|
|
|
2 |
p. 60-67 |
artikel |
5 |
Assessment of the atrial fibrillation burden in Holter electrocardiogram recordings using artificial intelligence
|
Hennings, Elisa |
|
|
|
2 |
p. 41-47 |
artikel |
6 |
Atrial fibrillation future clinic. Novel platform to integrate smart device electrocardiogram into clinical practice
|
Lambert, Cameron T. |
|
|
|
2 |
p. 92-100 |
artikel |
7 |
Can eHealth programs for cardiac arrhythmias be scaled-up by using the KardiaMobile algorithm?
|
Slaats, Bridget M.I. |
|
|
|
2 |
p. 78-84 |
artikel |
8 |
Circadian rhythm in critically ill patients: Insights from the eICU Database
|
Beyer, Sebastian E. |
|
|
|
2 |
p. 118-125 |
artikel |
9 |
Corrigendum to: Discriminating electrocardiographic responses to His-bundle pacing using machine learning [Cardiovascular Digital Health Journal 1 (2020) 11–20/5]
|
|
|
|
|
2 |
p. 111 |
artikel |
10 |
Deep learning to estimate cardiac magnetic resonance–derived left ventricular mass
|
Khurshid, Shaan |
|
|
|
2 |
p. 109-117 |
artikel |
11 |
Depressive symptoms are not associated with clinically important levels of digital home blood pressure in the electronic Framingham Heart Study
|
Lee, Jasmine |
|
|
|
2 |
p. 50-58 |
artikel |
12 |
Detecting paroxysmal atrial fibrillation from normal sinus rhythm in equine athletes using Symmetric Projection Attractor Reconstruction and machine learning
|
Huang, Ying H. |
|
|
|
2 |
p. 96-106 |
artikel |
13 |
Development and validation of a deep-learning model to predict 10-year atherosclerotic cardiovascular disease risk from retinal images using the UK Biobank and EyePACS 10K datasets
|
Vaghefi, Ehsan |
|
|
|
2 |
p. 59-69 |
artikel |
14 |
Digital health for primary prevention of cardiovascular disease: Promise to practice
|
Narla, Akhila |
|
|
|
2 |
p. 59-61 |
artikel |
15 |
Does sex modify an association of electrophysiological substrate with sudden cardiac death? The Atherosclerosis Risk in Communities (ARIC) study
|
Howell, Stacey J. |
|
|
|
2 |
p. 80-88 |
artikel |
16 |
Erratum
|
|
|
|
|
2 |
p. 150-151 |
artikel |
17 |
Identifying risk of adverse outcomes in COVID-19 patients via artificial intelligence–powered analysis of 12-lead intake electrocardiogram
|
Sridhar, Arun R. |
|
|
|
2 |
p. 62-74 |
artikel |
18 |
Impact of digital monitoring on compliance and outcome of lifestyle-change measures in patients with coexistent atrial fibrillation and obesity
|
Mohanty, Sanghamitra |
|
|
|
2 |
p. 75-79 |
artikel |
19 |
Implementation and early experience of a pediatric electrophysiology telehealth program
|
Schweber, Jonathan |
|
|
|
2 |
p. 89-95 |
artikel |
20 |
Latent profiles of telehealth care satisfaction during the COVID-19 pandemic among patients with cardiac conditions in an outpatient setting
|
van Schalkwijk, Dinah |
|
|
|
2 |
p. 85-95 |
artikel |
21 |
Letter from the Editor
|
McManus, David D. |
|
|
|
2 |
p. 55 |
artikel |
22 |
Letter from the Editor-in-Chief
|
McManus, David D. |
|
|
|
2 |
p. 91 |
artikel |
23 |
Letter from the Editors
|
McManus, David D. |
|
|
|
2 |
p. 61 |
artikel |
24 |
Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG
|
Luongo, Giorgio |
|
|
|
2 |
p. 126-136 |
artikel |
25 |
Patient Perspective: We should embrace digital health tools available since COVID
|
Rupp, Juddson |
|
|
|
2 |
p. 148-149 |
artikel |
26 |
Patient responses to daily cardiac resynchronization therapy device data: A pilot trial assessing a novel patient-centered digital dashboard in everyday life
|
Toscos, Tammy |
|
|
|
2 |
p. 97-106 |
artikel |
27 |
Performance comparison of 6 in-hospital patient monitoring systems in the detection and alarm of ventricular cardiac arrhythmias
|
Cosentino, Nicola |
|
|
|
2 |
p. 70-77 |
artikel |
28 |
Performance of an automated photoplethysmography-based artificial intelligence algorithm to detect atrial fibrillation
|
Mol, Daniel |
|
|
|
2 |
p. 107-110 |
artikel |
29 |
Postoperative atrial fibrillation: Prediction of subsequent recurrences with clinical risk modeling and artificial intelligence electrocardiography
|
Chamberlain, Alanna M. |
|
|
|
2 |
p. 111-114 |
artikel |
30 |
R-wave amplitude changes with posture and physical activity over time in an insertable cardiac monitor
|
Swale, Matthew |
|
|
|
2 |
p. 80-88 |
artikel |
31 |
Technology, community, and equity: Considerations for collecting social determinants data
|
Singh, Aditi |
|
|
|
2 |
p. 107-109 |
artikel |
32 |
Using digital health technology to evaluate the impact of chocolate on blood pressure: Results from the COCOA-BP study
|
Christen, Thomas |
|
|
|
2 |
p. 89-96 |
artikel |
33 |
Utilizing electronic health data and machine learning for the prediction of 30-day unplanned readmission or all-cause mortality in heart failure
|
Beecy, Ashley N. |
|
|
|
2 |
p. 71-79 |
artikel |
34 |
Visions for digital integrated cardiovascular care: HRS Digital Health Committee perspectives
|
Narayan, Sanjiv M. |
|
|
|
2 |
p. 37-49 |
artikel |
35 |
Wearables for arrhythmia care: Challenges and future prospects
|
Sarraju, Ashish |
|
|
|
2 |
p. 56-58 |
artikel |
36 |
“Wearables only work on patients that wear them”: Barriers and facilitators to the adoption of wearable cardiac monitoring technologies
|
Ferguson, Caleb |
|
|
|
2 |
p. 137-147 |
artikel |
37 |
Why digital health trials can fail: Lessons learned from a randomized trial of health coaching and virtual cardiac rehabilitation
|
Olivier, Christoph B. |
|
|
|
2 |
p. 101-108 |
artikel |