Clinical AI, Real-World Health Data (13M+ Patients) & Independent Validation | Horizon Europe Consortium Partner

DATA SCIENCE LAB | ANDALUSIAN PUBLIC HEALTH SYSTEM (SPAIN)

HORIZON EUROPE 2027 — CLINICAL AI, REAL-WORLD HEALTH DATA & INDEPENDENT VALIDATION

The Data Science Laboratory (LCD) of the Andalusian Public Health System, within the Progress and Health Public Foundation (FPS), seeks partnerships for Horizon Europe Cluster 1 – Health 2027 proposals.

We combine large-scale real-world health data, advanced Artificial Intelligence (AI), independent clinical algorithm validation and multidisciplinary healthcare expertise.

Our laboratory has contributed to 15+ AI projects, including 5+ Horizon Europe initiatives, and works with health data infrastructures covering over 13 million patients.

1. EXPERTISE AND CAPABILITIES

REAL-WORLD HEALTH DATA

We work with the Andalusian Population Health Database (BPS), covering 13M+ patients with longitudinal clinical, pharmaceutical, imaging and epidemiological information.

Our capabilities include:

• Real-world evidence and population health analytics.

• Longitudinal cohort studies and predictive modelling.

• Retrospective studies and external AI validation.

• Multimodal clinical data integration.

• Federated research and privacy-preserving analytics.

• GDPR, FAIR principles and EHDS-aligned governance.

Data access and secondary use require applicable legal, ethical and institutional authorisations.

ARTIFICIAL INTELLIGENCE AND PREDICTIVE MODELLING

We develop and evaluate clinical AI solutions using:

• Machine Learning and Deep Learning.

• NLP, Large Language Models (LLMs) and multimodal AI.

• Reinforcement Learning and Explainable AI (XAI).

• Predictive biomarkers and clinical risk stratification.

• Medical imaging analytics.

• Clinical Decision Support Systems (CDSS).

• Epidemiological forecasting.

We contribute from clinical problem definition and data engineering to algorithm development, benchmarking and clinical validation.

INDEPENDENT AI VALIDATION — EVIAS

Our laboratory operates EVIAS, an independent evaluation and benchmarking service for clinical AI algorithms.

We provide:

• Independent assessment of AI performance and robustness.

• External validation using real-world clinical data.

• Evaluation of safety, explainability and clinical applicability.

• Clinical benchmarking and reproducibility assessment.

• Evidence generation supporting regulatory evaluation under the EU AI Act and Medical Device Regulation (MDR).

CLINICAL EXPERTISE

We collaborate with healthcare professionals in oncology, intensive care, emergency medicine, cardiovascular diseases, infectious diseases, mental health, rare diseases, perinatal health, gastroenterology and public health.

2. EUROPEAN RESEARCH EXPERIENCE

Selected European projects:

• ASSESS-DHT (Horizon Europe): Digital health technology assessment methodologies.

• BRIDGE (IHI): Regulatory innovation and healthcare technology sandboxes.

• IntelliLung (Horizon Europe): Reinforcement learning-based clinical decision support for ICU ventilation.

• ePerinatal (Horizon Europe): Digital interventions and biomarkers for perinatal mental health.

• BRIDGE-ID (Horizon Europe): AI-supported diagnosis of rare neurodevelopmental diseases.

Additional initiatives:

• trIAje: AI and NLP applied to 12M+ emergency calls.

• ESCULAPIO: Population health data infrastructure and predictive analytics.

• COOPERATION SOUGHT

We seek partnerships with Horizon Europe coordinators, universities, hospitals, research institutions, public healthcare organisations, SMEs and digital health companies.

We aim to participate as a scientific, technical and clinical research partner, contributing to:

• AI development, predictive modelling and clinical decision support.

• Clinical data infrastructures, interoperability and governance.

• Real-world evidence and population health analytics.

• Independent AI validation and benchmarking.

• Multicentre studies and external clinical validation.

• Federated learning and EHDS-aligned research.

We are also open to leading technical work packages and supporting multidisciplinary clinical research.

5. CONTACT

Miguel Ángel Armengol de la Hoz, PhD
Head of the Data Science Lab
Progress and Health Public Foundation (FPS)
Andalusian Public Health System
Government of Andalusia, Spain

Email: mangel.armengol@juntadeandalucia.es
ORCID: 0000-0002-7012-2973

We welcome collaboration with European consortia seeking expertise in clinical AI, real-world health data, predictive modelling and independent AI validation.