Heart Failure AI in 2025: Are We Getting More Intelligent?

The era of predictive modeling, machine learning, and artificial intelligence to enhance clinical decision-making through the identification and treatment of disease is fully underway. From imaging and ECG acquisition/interpretation algorithms to the use of large language models for ambient listening, rapid chart review, and generation of evidence-based recommendations, healthcare systems are abuzz with how AI can improve outcomes and reduce clinician burden. This session aims to provide timely updates on the current and future state of clinical AI.

Agenda

• Moderator - Ramsey Wehbe, MD, MSAI
• Moderator - ByungSu Yoo, MD
• Diagnostic Testing to Clinical Phenotyping: Lessons Learned and Future Directions - Ambarish Pandey, MD
• Risk Prediction and Clinical Decision Support: Is AI Ready for the Frontline? - Alexander Sandhu, MD, MS
• Automating Chart Review: Deployment of Large Language Models for Clinical Care and Research - Trejeeve Martyn, MD
• Remote Heart Failure Monitoring: Is AI Ready to Help Us? - Jessica Golbus, MD
• Question and Answer