SOURCE-LINKED INTELLIGENCE

Enabling Decentralised Digital Twin Era in existing Research Infrastructures for Predictive, Preventive, Personalised, and Participatory Health

CORDIS · observation · Publication date unknown

sisting of RIs”. Using DTs, we aim to resolve critical challenges around data harmonization, equitable access, and stringent privacy safeguards. Incorporating technologies such as federated learning, Generative AI, and Virtual Reality (VR), the project aspires to create a decentralized digital twin environment (DDTE). This will empower both internal and external RI users, such as researchers, innovators, and SMEs, to craft DT applications that address specific scientific challenges, utilizing a blend of real-world and synthetic data in compliance with regulatory frameworks, i.e. GDPR. We will develop 7 innovative proof of concept thematic health-related Use cases fulfilling the needs of scientists, SMEs, and industrial end users, particularly in health topics related to cancer treatment, drug development, human environmental exposome, precision treatment for schizophrenia and personalized medicine through Artificial Intelligence (AI), AR/VR empowered DTs utilizing DDTE, while adhering to FAIR data principles. DTRIP4H adopts a human-centric methodology to elevate research efficacy, n

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

11998387.21

unit

EUR