CredenceX Ai Research Lab

Accuracy is easy to advertise. Trust is harder to earn.

In healthcare, a confident-but-wrong prediction can be harmful. That’s why at CredenceX AI Research Lab we build medical imaging systems that:
(i) Explains its decisions with clear, evidence-based outputs
(ii) Reports uncertainty—so clinicians know when to trust a result and when to review
(iii) Generalizes across hospitals and scanners, not just one dataset

📚 Explore our publications: https://www.credencex.ai/publications

We’ve Launched Our Official Website!

At CredenceX, we create trustworthy AI for medical imaging that aids in early detection, clinical decision-making, and safe deployment in critical healthcare environments. Our models are designed to be consistent across various hospitals, scanners, and patient demographics, providing clear explanations and indicating uncertainty so that clinicians and patients can determine when to trust the results.

On our website, you can explore:
Core Research Areas (Vision + Language for Healthcare, Explainable Imaging AI, Trustworthy & Risk-Aware AI, and more)
Projects (active, completed, and planned)
Publications & Research Outputs
Team, News, and Collaboration Updates
If you’d like to collaborate, partner, or connect—reach out through the Contact page.

Visit us: https://www.credencex.ai/

Launching CredenceX — a research lab building data-driven systems that sense, reason, and assist in delivering early warning, decision support, and risk-aware security for high-stakes AI applications.

Our early focus includes:
(i) Medical imaging + VLMs: multimodal foundation models and multimodal fusion (images + reports + clinical context).
(ii) LLMs with RAG & agents: tool-using workflows with safety guardrails.
(iii) Trustworthy AI: uncertainty, explainability, robustness, privacy-preserving ML.
(iv) Cyber security: prompt-injection resistance, adversarial robustness, anomaly detection, zero-trust-aligned monitoring.

We’ll share our first projects soon. Follow and share to support the journey.