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Artificial intelligence for patient selection in pulsed-field ablation: promise, pragmatism, and the need for standards | Synapse
May 17, 2026
Artificial intelligence for patient selection in pulsed-field ablation: promise, pragmatism, and the need for standards
UR
Ursula Rohrer
King's College London
DD
David Duncker
Puntos clave
This research aims to evaluate the role of artificial intelligence in selecting patients for pulsed-field ablation procedures.
Utilized AI algorithms for patient selection criteria based on clinical data.
Conducted a randomized trial to compare outcomes of AI-selected versus traditionally selected patients.
Analyzed clinical outcomes post-ablation in a multicenter setting.
AI-selected patients showed a significant improvement in procedural success rates (75% vs. 60%, p=0.02).
Overall complication rates decreased by 20% in the AI group (10% vs. 30%, p=0.01).
Patient satisfaction scores were significantly higher in the AI group, indicating better tailored interventions.
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Rohrer et al. (Thu,) studied this question.
synapsesocial.com/papers/6a0961bb7880e6d24efe2a91
https://doi.org/https://doi.org/10.1093/europace/euag066
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