Role of Artificial Intelligence in Reducing Data Deluge From Cardiac Implantable Electronic Devices
This study presents a real-world analysis of incorporating AI in device clinic workflow to assist in interpretation and classification of RM data. AI interpretation of transmissions was found to have an accuracy similar to that of DT with superior sensitivity but lesser specificity.
Authors
- Rachad Ghazal (ORCID: https://orcid.org/0009-0001-4790-5283)
- Adnan Ahmed (ORCID: https://orcid.org/0000-0001-5442-6929)
- Shanti Bansal
- Dhanunjaya Lakkireddy (ORCID: https://orcid.org/0000-0002-1492-2693)
- Nicholas Pham (ORCID: https://orcid.org/0000-0002-0342-1770)
- Danish Bawa (ORCID: https://orcid.org/0000-0002-8753-822X)
- Naga Venkata K. Pothineni (ORCID: https://orcid.org/0000-0003-4908-2652)
- Aashish Katapadi (ORCID: https://orcid.org/0000-0003-4193-2130)
- Ilyas Colombowala
- Rajesh Kabra (ORCID: https://orcid.org/0000-0002-5118-2962)
- Douglas Darden
- Rakesh Gopinathannair (ORCID: https://orcid.org/0000-0003-4611-3687)
- Mina K. Chung (ORCID: https://orcid.org/0000-0002-7835-6045)
Institutions
- Heart Rhythm Society (US)
- Cleveland Clinic (US)
- West Health (US)
Publication Details
- Journal
- JACC Advances
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1016/j.jacadv.2025.102057
- Citations
- 1
- Primary Topic
- Cardiac pacing and defibrillation studies
- Type
- article
- Field-Weighted Citation Impact
- 1.39