OasisLMS

As AI begins to transform the EP landscape, high-quality data collection in the EP laboratory has become a foundational requirement. However, the process of collecting, structuring, labeling, and integrating multimodal EP data—including signals, imaging, annotations, and procedural metadata—presents significant technical, regulatory, and operational challenges. This roundtable will convene EP clinicians, data scientists, digital health leaders, and industry innovators to explore how data generated during routine EP procedures can be leveraged to power AI algorithms. Topics will include interoperability between EP lab systems, data ownership and governance, strategies for annotation and ground truth creation, privacy-preserving data sharing, and collaborative AI development between health systems and industry. Panelists will also showcase early successes and lessons learned from existing AI initiatives in arrhythmia detection, ablation guidance, and post-procedure outcomes prediction.

Moderator
Nassir Marrouche 

Presenters
Tina Baykaner 
Alexandre Almorad, Brussels 
Kalyanam Shivkumar 
Hee Tae Yu
Yitzi Pfeffer 
Maulik Nanavaty