The Data Science Lab (LCD) is a research and innovation unit within the Progress and Health Foundation (FPS), part of the Andalusian Regional Government's public health research and innovation system in Spain.
The Lab specialises in applying artificial intelligence (AI), machine learning, deep learning, and advanced data analytics to healthcare, with a focus on transforming routinely collected clinical data into evidence that supports clinical research, healthcare decision-making, and the development of AI-based medical technologies.
Our core areas of expertise include:
-
AI and predictive modelling in healthcare: Development, validation, and evaluation of machine learning models for clinical risk prediction, patient stratification, disease progression, treatment response, and clinical decision support.
-
Real-World Data and Real-World Evidence (RWD/RWE): Secondary use of electronic health records, clinical registries, and administrative healthcare databases for observational research and evidence generation.
-
Health data infrastructures and interoperability: Development of clinical data repositories, data harmonisation pipelines, and analytical infrastructures supporting multicentre research and federated data analysis.
-
Clinical AI validation: Retrospective and prospective evaluation of AI-based technologies, including clinical performance, generalisability, bias, and applicability in healthcare settings.
-
European Health Data Space (EHDS): Research and innovation activities supporting health data interoperability, secondary data use, and cross-border collaboration.
Clinical application areas
Our research covers critical care, emergency medical services, cardiovascular and cerebrovascular diseases, respiratory conditions, infectious diseases, antimicrobial resistance, immune-mediated inflammatory diseases, and population health.
European research and collaboration
The Lab participates in European research initiatives, including IntelliLung, ASSESS-DHT, and BRIDGE, contributing expertise in clinical data analytics, AI development and validation, real-world evidence, and digital health technology assessment.
Our work combines expertise in data science, biomedical engineering, and clinical research through collaborations with healthcare professionals, hospitals, academic institutions, and technology partners.
What we offer to Horizon Europe consortia
The Data Science Lab is interested in joining international research and innovation consortia, particularly those addressing:
-
AI-based biomarkers and predictive models for chronic diseases.
-
Development and external validation of clinical AI solutions.
-
Multicentre observational studies and real-world evidence generation.
-
Federated learning, data interoperability, and secondary use of health data.
-
Digital health technology assessment and AI evaluation methodologies.
-
Clinical decision support systems and precision medicine.
-
Responsible AI, model generalisability, and reproducible clinical research.
Through FPS and its collaborations within the Andalusian Public Health System, the Lab can contribute expertise in health data analysis, clinical research methodologies, AI development, and coordination with healthcare stakeholders.
We welcome collaborations with research organisations, hospitals, universities, SMEs, technology developers, and European consortia seeking expertise in AI and health data science.