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Research in Generative Artificial Intelligence to develop a clinical copilot that supports healthcare professionals in diagnostic and decision-making processes. To this end, research, the design and the validation of an architecture able to adapt to new contexts through novel techniques that reduce bias and hallucinations in the context of cardiac conditions will be required.

The methodological approach is based on the research and comparison of different generative artificial intelligence architectures and techniques, with a special focus on Domain Adaptation of Large Multimodal Models (LMM) applied to the clinical domain, such as fine-tuning, advanced contexts and prompt engineering. The objective is to identify the most suitable strategy to integrate, in a balanced way: (i) robust mechanisms for the retrieval and use of medical evidence, (ii) models adapted to the linguistic and clinical context of real healthcare practice, and (iii) the generative ability to offer explainable and traceable recommendations, always grounded in verifiable evidence. The research will make it possible to adapt large generative models to highly specific tasks, such as clinical diagnosis targeted at rural populations in Colombia, thereby reducing the likelihood of hallucinations and problems arising from bias.

Avenida Cataluña, 11 Entlo. (Valencia)

01/01/2026 to 31/12/2027

Omniloy S.L. has completed its advanced effective onboarding as a provider to the MIRACLE Data Space, promoted by the Universitat de València through IRTIC, with the aim of joining a sector-specific environment for sharing healthcare data focused specifically on robotic surgery, medical imaging and the development of AI systems for surgical support. The choice of MIRACLE reflects the coherence between the technological specialization of the space and Omniloy's ability to contribute valuable digital assets within an interoperable, secure framework aligned with the European principles of data sovereignty, controlled reuse and health innovation.

C055/25-SI Data Spaces Kit: Digital transformation of strategic productive sectors by fostering the adaptation and onboarding of participants into data spaces (File No.: 2026/C055/05816634)

L2. Incorporació. Incorporation of research and technology staff for innovation projects in companies.

The project's objective is to hire research staff to develop SofIA, an intelligent clinical assistant based on generative AI that incorporates advanced capabilities such as the automated synthesis of the patient's clinical history, contextual responses to medical queries, precise diagnostic coding, automatic report generation and the direct structuring of data into the hospital information system (HIS).

This solution will help address several of the strategic challenges identified in the mentioned priority, including the optimisation of clinical processes, support for medical decision-making and the reduction of errors through automation and the contextual analysis of unstructured clinical data.