The Center offers institutions, healthcare organizations, research bodies, associations, and companies a portfolio of services for the design, prototyping, evaluation, validation, and responsible adoption of digital health and AI solutions.
Analysis and mitigation of the cognitive, emotional, relational, organizational, and ethical effects associated with the introduction of AI systems in professional settings.
Support in evaluating the effects of AI systems on privacy, autonomy, equity, non-discrimination, transparency, contestability, human oversight, and access to services.
Analysis of the technical, organizational, cultural, and governance conditions required to adopt AI responsibly, effectively, and sustainably.
Assessment of whether an AI solution can be concretely implemented, used, monitored, governed, and maintained in real operational contexts.
Study of processes, requirements, constraints, and socio-technical conditions that may enable or hinder the introduction of digital technologies and AI
Participatory design of immersive and multimodal health applications grounded in clinical protocols and oriented towards safety, efficacy, and integration into care pathways.
Design of feasibility studies, clinical protocols, outcome measures, and ethical-regulatory documentation for DTx, clinical chatbots, and immersive digital interventions.
Analysis, design, and validation of autonomous agents and agentic pipelines for multi-step processes, with attention to oversight, accountability, escalation, and organizational sustainability.
Design and validation of conversational solutions combining retrieval-augmented generation, reliable knowledge bases, source attribution, and lifecycle governance.
Design and development of secure, interoperable, and scalable architectures for clinical applications, CDSS, DTx, and digital services integrated into healthcare workflows.
Support for living labs, proof-of-concept development, rapid prototyping, interoperability testing, usability studies, field validation, and transfer into operational use.
Design and testing of interactive visualizations for interpreting complex clinical and biological data, disease trajectories, care pathways, and sample evolution.
Creation and validation of multimodal synthetic data, virtual patients, clinical simulations, and in silico training or experimentation environments.
Design, training, and verification of predictive modules for diagnosis, prognosis, risk stratification, and personalized therapeutic planning.