The KG4Health workshop addresses the critical intersection of Knowledge Graphs (KGs) and Artificial Intelligence in the biomedical and healthcare domain. While modern AI models (i.e., Generative AI) have shown immense potential in processing healthcare data, clinical text, and biomedical information issues regarding factual accuracy, explainability, and data siloization persist. Knowledge Graphs provide a structured, interpretable foundation that can ground AI models in established medical truths. We welcome computer scientists, medical informaticians, and clinicians to submit their late-breaking results, demos, or position statements via OpenReview to join this high-intensity, half-day dialogue on the future of evidence-based, explainable medical AI.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome.

• Full papers (6-8 pages).
• Demo, Short, Position, or Vision papers (4-6 pages).

List of Topics

• KG-LLM Integration: Methods for embedding KGs into LLMs to enhance factual grounding and reasoning in medical applications.
• Neuro-symbolic AI: Combining LLMs with KGs (e.g., Retrieval-Augmented Generation - RAG) for medical QA.
• KG Construction & Enrichment: Automated extraction of medical entities/relations from clinical notes and literature.
• Interoperability: Mapping KGs to standard ontologies (SNOMED-CT, UMLS, FHIR).
• Explainable AI (XAI): Using graph paths to provide the "why" behind AI-driven clinical predictions.
• Medical Applications of KG: Drug repurposing, rare disease diagnosis, and personalized treatment pathways.

Committees

Program Committee

• Fatemeh Bagheri, Saint Mary's University, Canada
• Zhendong Sha, Cleveland Clinic Research, USA
• Ahmet Soylu, Kristiania University College, Norway
• Hannah Kim, Temple University, USA
• Akhil Chaudhary, Toronto Metropolitan University, Canada
• Faezeh Ensan, Cape Breton University, Canada
• Christophe Debruyne, University of Liège, Belgium
• Majid Ziaratban, Saint Mary's University, Canada
• Jaber Rad, Dalhousie University, Canada
• Allard Oelen, German National Library of Science and Technology, Germany
• Hande Küçük McGinty, Kansas State University, Manhattan, KS, USA
• Zaynab Mousavian, Emory University, USA

Organizing Committee

• Enayat Rajabi, Cape Breton University, Canada
• Somayeh Kafaie, Saint Mary's University, Canada

Venue

The conference will be held in University of Ottawa (uOttawa), Canada. For more information about the conference venue, please refer to the AIME2026 website.