Back

An LLM-native Wiki knowledge graph for HFpEF: structured, traceable clinical question answering in a complex cardiovascular syndrome

13 November 2026 (11:30 - 12:15)
Organised by: Logo
Add to my library
Congress Presentation Part of: Can a large language models reason like a cardiologist? Large Language Model Delegates Premium Access ESC Digital & AI Summit 2026 European Society of Cardiology

About the speaker

Photo
Miss Sarah Kaye Mueller

Artificial Intelligence in Cardiovascular Medicine, Heidelberg (Germany)

6 More presentations in this session

Presentation thumbnail
Replacing the people who promised to replace clinicians: autonomous AI-agents for cardiac MRI segmentation
Mr M. Seyfarth (Heidelberg, DE)
Abstract Slides
Presentation thumbnail
Analysis of locally deployed open-source large language models for diagnosis extraction from CMR reports
Mr S. Amirrajab (Maastricht, NL)
Abstract Slides
Presentation thumbnail
Navigating a smart cardiac MRI viewer with LLM-driven natural language control
Mr M. Vroemen (Eindhoven, NL)
Abstract Slides
Presentation thumbnail
Large language model-assisted case finding for hypertrophic cardiomyopathy: identifying patients eligible for specialist review from routine clinical documentation
Mr R. Schweitzer (London, GB)
Abstract Slides
Presentation thumbnail
Incentivising cardiologist-like reasoning in MLLMs for interpretable echocardiographic diagnosis
Mr Y. Qin (Tseung Kwan O, HK)
Abstract Slides

Access the full session

Session thumbnail
Can a large language models reason like a cardiologist?

The Event

Event poster

ESC Digital & AI Summit 2026

13 November 2026 11:30 CET
You may be interested in
thumbnail
Congress Presentation
LLM powered echocardiography report structuring: a step towards precision medicine
1 September 2025
thumbnail
Congress Presentation
Uncovering knowledge and practice gaps in heart failure with preserved ejection fraction
30 June 2021
thumbnail
Congress Presentation
Large language model Wiki: build your own knowledge graph
13 November 2026
thumbnail
Congress Presentation
Artificial intelligence methods to detect heart failure with preserved ejection fraction (AIM-HFpEF) within electronic health records: an equitable disease prediction model
1 September 2025

ESC 365 is supported by

Lilly Explore sponsored resources
novartis Explore sponsored resources
novo-nordisk Explore sponsored resources

ESC 365 is supported by

Lilly Explore sponsored resources
novartis Explore sponsored resources
novo-nordisk Explore sponsored resources