| 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
|
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