From Big data to new science and practical solutions

Información del proyecto

Data4Healthcare

Identificador del acuerdo de subvención: 101126602

DOI

10.3030/101126602

Fecha de la firma de la CE 18 Octubre 2023

Fecha de inicio 1 Enero 2024

Fecha de finalización 31 Diciembre 2028

Financiado con arreglo a

• Marie Skłodowska-Curie Actions (MSCA)

Coste total

Sin datos

Aportación de la UE

€ 3 582 000,00

Coordinado por

OULUN YLIOPISTO
Finland

Periodic Reporting for period 1 - Data4Healthcare (From Big data to new science and practical solutions)

Período documentado: 2024-01-01 hasta 2025-12-31

Resumen del contexto y de los objetivos generales del proyecto

Data4Healthcare is a novel postdoctoral programme hosted at the University of Oulu, Finland. The programme was established to train 25 postdoctoral researchers who can work with advanced data technologies, such as big data analytics, machine vision, and artificial intelligence. In doing so, the programme aims to response a growing need: we simply do not have enough specialists who can turn today’s massive health datasets into useful knowledge that benefits people. With the help of the OuluHealth ecosystem, bringing together strong ICT know‑how, extensive molecular data, and one of the world’s most advanced digital hospital, the programme offers researchers an excellent environment to develop new solutions for future healthcare.
The programme aims to:
• Train a new generation of experts in data driven healthcare.
• Support research that contributes to better diagnostics, prevention, and wellbeing.
• Strengthen Europe’s capacity to use big data responsibly.
• Connect research with clinical and real world needs.
• Help build healthier, more resilient societies.
• Enhance international and intersectoral mobility by enabling researchers to work across countries, disciplines, and sectors

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

The programme has successfully completed two highly competitive international recruitment rounds, which attracted strong interest from around the world. Through an open, transparent, and merit based evaluation process involving international peer reviewers, a total of 25 postdoctoral researchers were selected.
These researchers have now launched a diverse set of high‑impact projects, exploring topics such as:
• AI-assisted diagnostics and digital pathology.
• Rare-disease genetics and multi omics.
• Wearable and sensor-based health monitoring.
• Environmental and planetary health analytics.
• Data-driven public-health modeling.
Although many of the projects are still in their early phases, the fellows have already become active members of the scientific community. They have presented their work at international conferences and have contributed to the first scientific publications emerging from the programme.
To support their development, a comprehensive training curriculum has been established. All fellows are offered specialized training in responsible data use, artificial intelligence, and advanced analytics, ensuring they have the skills needed to carry out high quality research and to contribute to innovation in modern healthcare.

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

The scientific and technological developments emerging from the Data4Healthcare programme have strong potential to influence the future of healthcare and wellbeing. The programme creates a clear connection between advanced data science and real clinical practice, helping to turn complex research into practical solutions. This work is already paving the way for:
• Earlier disease detection using new AI‑based digital tools
• More precise and personalised treatments through deeper insights gained from multi‑omics data
• Innovative health monitoring using wearable technologies and nanotechnology for faster diagnostics.
• Evidence-based decision-making in public health through improved environmental-health models.
As the projects progress, their outcomes may lead to new algorithms, datasets, prototypes, and health technology innovations. These could eventually be used in hospitals, clinics, public health systems, and industry. By training researchers in Open Science, intellectual property management, and innovation processes, the programme ensures that scientific discoveries do not remain in the laboratory. Instead, they can be transformed into practical tools, prototypes, and clinical solutions that bring real benefits to healthcare across Europe.