HetERogeneous sEmantic Data integratIon for the guT-bRain interplaY
HetERogeneous sEmantic Data integratIon for the guT-bRain interplaY
About HEREDITARY Project
Our goal is to change the way we approach healthcare by unlocking insights that were previously impossible to obtain
HEREDITARY aims to improve disease detection, treatment response preparation, and medical knowledge exploration through an integrated framework that incorporates diverse health data, including genetics, while ensuring privacy compliance.
Its five-layered structure enables advanced federated analytics to uncover new insights into neurodegenerative and gut microbiome-related disorders.
By harmonizing clinical, genomic, and environmental data on a large scale, HEREDITARY seeks to empower clinicians, researchers, and policymakers to develop more effective treatment and diagnosis strategies.
Our objectives
Secure distributed system for multimodal health data linkage
To develop a federated, scalable, secure, and privacy-preserving system for linkage of health data enabling querying of multimodal data across sources and disease groups.
Semantics-aware learning methods integrating multimodal & genomics data
To develop advanced analytics and learning methods for a better understanding of the risk factors, causes, development and optimal treatment for disorders related to the gut-brain interplay.
Interactive data-driven solutions
To develop data-driven and evidence-based solutions to empower decision-making, prevention, information campaigns and strengthen citizen‘s trust.
Key outcomes
FEDERATED LEARNING AND ANALYTICS
A shared framework for secure & lawful federated access to linked multimodal health data across Europe and beyond allows healthcare data normalization libraries targeting data formats, quality, and interoperability.
MULTIMODAL ONTOLOGY
A multimodal ontology for healthcare targeting gut-brain interplay, using privacy-aware federated learning models and federated semantic polystore to integrate and query multimodal health and genomics data.
VISUAL ANALYTICS
A visual analytics platform to discover and aggregate data from multiple sources for multiple groups of diseases, which brings evidence-based recommendations for patients and citizens.
FEDERATED LEARNING AND ANALYTICS
A shared framework for secure & lawful federated access to linked multimodal health data across Europe and beyond allows healthcare data normalization libraries targeting data formats, quality, and interoperability.
MULTIMODAL ONTOLOGY
A multimodal ontology for healthcare targeting gut-brain interplay, using privacy-aware federated learning models and federated semantic polystore to integrate and query multimodal health and genomics data.
VISUAL ANALYTICS
A visual analytics platform to discover and aggregate data from multiple sources for multiple groups of diseases, which brings evidence-based recommendations for patients and citizens.
Pillars of HEREDITARY
Medical dimension
HEREDITARY focuses on diseases involving the complex gut-brain interplay, to identify new risk factors, treatment responses, and to increase public awareness. Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), Parkinson’s (PD), Alzheimer’s (AD), Frontotemporal Dementia (FD), stroke, diabetes, obesity and psychiatric disorders, like depression or ADHD will be among the diseases studied.
Technical dimension
To integrate diverse health data through a five-layer framework that ensures privacy, scalability, and advanced analytics. Using AI and machine learning, the project harmonizes multimodal data from clinical partners, while ensuring data security and compliance with regulations.
Social dimension
The Health Social Labs initiated by the project will facilitate the co-design of the HEREDITARY architecture with patients, citizens, and domain experts, following an effective path of citizen science. These forums will encourage discussions, comparisons, and proposals to ensure popularization, communication, and dissemination of results are as inclusive as possible.
Legal aspects
The federated system framework will pay attention to relevant legal and ethical requirements such as those stemming from the AI Act Proposal, the GDPR, and ethical principles on AI.