Auditability · Explainability · Trustworthiness

Advancing Biomedical Data Science through Transparent, Explainable, and Trustworthy AI

BetterHealth = f(TrustWorthyAI)

Skyline: King of Hearts / Wikimedia Commons, CC BY-SA 3.0. Cropped and resized.

Current research

Active Projects

Selected initiatives that demonstrate the lab's focus on auditable, explainable, and trustworthy biomedical AI.

A defining research pillar

Benchmarking & Evaluation

We develop rigorous evaluation frameworks that make biomedical AI and data infrastructure more measurable, comparable, auditable, and trustworthy.

Selected scholarship

Recent work spanning trustworthy clinical AI, interoperability, biomedical knowledge engineering, and rigorous evaluation.

Open research infrastructure

Software & Resources

A curated selection from the lab's broader portfolio of research software, standards, and knowledge-engineering tools.

From the lab

News