Artificial intelligence-guided mapping of persistent atrial fibrillation: Complementary to or better than the electrophysiologist?
- PMID: 38351476
- DOI: 10.1111/jce.16214
Artificial intelligence-guided mapping of persistent atrial fibrillation: Complementary to or better than the electrophysiologist?
Keywords: artificial intelligence; atrial fibrillation; mapping; mechanisms.
References
REFERENCES
-
- Open AI. ChatGPT (Mar 14 version) [Large language model]. 2023. https://chat.openai.com/chat
-
- Feeny AK, Rickard J, Patel D, et al. Machine learning prediction of response to cardiac resynchronization therapy: improvement versus current guidelines. Circ Arrhythmia Electrophysiol. 2019;12(7):e007316.
-
- Alhusseini MI, Abuzaid F, Rogers AJ, et al. Machine learning to classify intracardiac electrical patterns during atrial fibrillation. Circ Arrhythmia Electrophysiol. 2020;13:e008160.
-
- Seitz J, Durdez TM, Albenque JP, et al. Artificial intelligence software standardizes electrogram-based ablation outcome for persistent atrial fibrillation. J Cardiovasc Electrophysiol. 2022;33:2250-2260.
-
- Bahlke F, Englert F, Popa M, et al. First clinical data on artificial intelligence-guided catheter ablation of long-standing persistent atrial fibrillation. J Cardiovasc Electrophysiol. 2024;35:406-414. doi:10.1111/jce.16184
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