Secure Distributed System for Multimodal Health Data Linkage

The HEREDITARY project aims to create a secure and distributed system for linking multimodal health data. This system ensures that data from various sources, such as electronic health records, genomic data, medical imaging, and environmental data, can be securely integrated and accessed. The project’s innovative approach involves using secure supercomputer environments to facilitate federated learning, where data remains localized but can be analyzed collaboratively. This method respects privacy and regulatory requirements, such as GDPR, ensuring that sensitive health data does not cross organizational boundaries. By providing a unified infrastructure, HEREDITARY enables the seamless linking and analysis of diverse health data, crucial for advancing medical research and improving patient outcomes.

Semantics-Aware Learning Methods Integrating Multimodal & Genomics Data for Improving Health Outcomes

HEREDITARY focuses on developing semantics-aware learning methods that integrate multimodal and genomics data to enhance health outcomes. By leveraging cutting-edge machine learning and AI techniques, the project aims to create comprehensive data representations that can inform disease detection, treatment, and prevention strategies. This involves the use of Ontology-Based Data Access (OBDA) to unify different data types and sources, enabling complex queries and predictive analytics. The project will employ advanced learning models, such as deep neural networks and self-supervised learning, to analyze data across various modalities, including text, images, and genomic sequences. These efforts will provide deeper insights into the gut-brain axis and its impact on neurodegenerative diseases and related disorders, ultimately leading to better personalized medicine and healthcare solutions.

Interactive Data-Driven Solutions to Empower Decision-Making, Prevention, and Strengthen Citizen's Trust

The HEREDITARY project aims to empower decision-making and strengthen citizen trust through interactive data-driven solutions. This involves the development of a visual analytics and interaction platform that allows researchers, clinicians, and policymakers to access and analyze complex health data easily. The platform integrates advanced visual analytics with interactive data visualization, facilitating data exploration, hypothesis testing, and presentation of findings. By providing transparent and explainable AI methods, HEREDITARY ensures that users can trust and understand the analytical processes and results. The project also emphasizes citizen engagement, involving patient organizations and the public in the research process to increase awareness and acceptance of the findings. These efforts aim to enhance public trust in data-driven healthcare innovations and promote informed decision-making for better health outcomes.