Publications

Research you can build on

Frameworks and papers advancing transparent, auditable medical AI.

The DREAM vision

Model the system, not just the output

MedTWIN.AI is grounded in a physiology-first approach: a modular architecture where decisions are traceable, computation is deterministic, and models evolve with evidence.

Cross-specialtyPhysiology-firstTransparent AI

Latest papers

A small but focused set of publications to ground the product and platform.

PublishedFeatured

Chain-of-Thought Reasoning for Adaptive Clinical Digital Twins

Exploring how chain-of-thought style reasoning traces can improve transparency and reduce failure modes in clinical digital twin systems.

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Published

A Next-Generation Framework for Adaptive, Transparent Clinical Decision-Support

A blueprint for clinical decision-support that prioritizes transparency, adaptability, and physiological grounding instead of opaque correlation-only models.

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Want to collaborate?

We’re looking for clinical and research partners to stress-test workflows and governance in real datasets.

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