SOURCE-LINKED INTELLIGENCE
Multimodal Digital TWINs with Generative AI for eXplainable Precision Medicine
Multimodal Digital TWINs with Generative AI for eXplainable Precision Medicine TWIN-X will build an interactive digital patient twin for oncology and cardiology that integrates imaging, clinical narratives, laboratory data and pathology to support precision medicine. The twin is a modular, clinically coherent representation that clinical researchers can interrogate and update through transparent queries, what if simulations and counterfactual exploration. Users can compare therapeutic options and timing, inspect predicted trajectories with calibrated uncertainty, trace outputs to underlying evidence and receive concise, verifiable rationales generated from structured sources. Generative AI first structures data before embedding to preserve clinical meaning and enable faithful explanations. Trust is ensured through end to end calibration, out of distribution detection, selective abstention, human oversight and equity
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 14997371.25
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T05:31:32.981Z. This is not the publication date.