Gordon Research Conference on Cardiac Arrhythmia Mechanisms 2023: early career investigators’ views on emerging concepts and technologies-Reference-Cited by-同舟云学术

Gordon Research Conference on Cardiac Arrhythmia Mechanisms 2023: early career investigators’ views on emerging concepts and technologies

Published:2023-07-18 Issue: Volume: Page:
ISSN:0022-3751
Container-title:The Journal of Physiology
language:en
Short-container-title:The Journal of Physiology

Author:

Ramadan Ahmed¹^ORCID,Chleilat Enaam²^ORCID,Martinez‐Navarro Hector³^ORCID,Brennan‐McLean Jaclyn⁴^ORCID,Copier Jaël⁵^ORCID,Caldwell Jessica⁶^ORCID,Greiner Joachim²^ORCID,Martínez Díaz Patricia⁷^ORCID,Sobota Vladimír⁸^ORCID

Affiliation:

1. School of Biomedical Engineering Dalhousie University Halifax Nova Scotia Canada

2. Institute for Experimental Cardiovascular Medicine University Heart Center Freiburg Bad Krozingen, and Medical Faculty of the University of Freiburg Freiburg Germany

3. Department of Computer Science, British Heart Foundation Centre of Research Excellence University of Oxford Oxford UK

4. American Association for the Advancement of Science (AAAS) Science and Technology Policy Fellowships Program Washington DC USA

5. Amsterdam UMC location University of Amsterdam, Experimental Cardiology, Amsterdam Cardiovascular Sciences Heart failure & arrhythmias Amsterdam The Netherlands

6. Department of Pharmacology University of California Davis Davis California USA

7. Karlsruhe Institute of Technology (KIT) Institute of Biomedical Engineering Karlsruhe Germany

8. IHU Liryc, Electrophysiology and Heart Modeling Institute Fondation Bordeaux Université Bordeaux France

Publisher

Wiley

Subject

Physiology

Link

https://physoc.onlinelibrary.wiley.com/doi/pdf/10.1113/JP284666

Reference23 articles.

1. Random access parallel microscopy

2. Personalized ablation vs. conventional ablation strategies to terminate atrial fibrillation and prevent recurrence

3. Raise standards for preclinical cancer research

4. PO-690-02 ABLATION SCAR ARRHYTHMOGENICITY CAN BE PREDICTED BY AN EXPLAINABLE MACHINE LEARNING (ML) CLASSIFIER: PROOF-OF-CONCEPT FROM COMPUTATIONAL SIMULATIONS

5. The Heart’s Pacemaker Mimics Brain Cytoarchitecture and Function