Unleashing the power of Artificial Intelligence

An open source data hub for haematological diseases

GenoMed4All goes beyond the state-of-the-art to diagnose, treat and predict haematological diseases by adopting groundbreaking and trustworthy AI algorithms. Our precision medicine model will feature Federated Learning and High-Performance Computing (HPC) to become more reliable when simulating and predicting patterns that might reveal weaknesses and risks.

Our core principles


Using Graph Neural Networks to distributedly train deep learning algorithms


Enabling collaborative, cross-border data sharing that is standard-compliant


Offering security and privacy by design in all data exchanges, model training and storage


Using containerization to build modularity and facilitate massive replicability

What are we aiming for?


Clinical repositories with genomics data connected across 15 EU countries


Accuracy improvement in specific genomic markers for prognosis and treatment


Increase in the adoption of open standards for -omics data per clinical site


Time reduction in AI analysis and model training through Supercomputing

Linking -omics and clinical data repositories across Europe

The project will build a large-scale distributed repository of -omics health data across Europe, including: Electronic Health Record, PET, MRI and CT, Next Generation Sequencing, Microarray, Genome-Wide Association, Copy Number Variations, DNA and RNA sequencing. This scheme will enable the aggregation of a high number of repositories that are currently dispersed and non-homogenised while respecting the patient's rights

More accurate Deep Neural Networks regression and classification models

Explicit features extraction using advanced generative models such as Variational Autoencoders and Generative Adversarial Networks

Optimal fusion architectures using heterogeneous data as a combination of feedforward, convolutional and recurrent networks

Exploring new models in genomics for personalised medicine

GenoMed4All will deploy 'white box' AI models in 3 real-world pilots, improving the diagnosis and prognosis capacity, evaluating treatment options and patient response. The pilots will cover common and rare oncological (Myelodysplastic syndromes and Multiple Myeloma) and non-oncological (Sickle Cell Disease) haematological diseases

AI- based services for clinical support


AI algorithms for early identification of high-risk individuals


Prediction algorithms for insights on disease development


Clinical algorithms to aid decision-making in risk stratification of personalized therapies


The EU dimension

Transforming Health and Care in the Digital Single Market

EU policies on eHealth aim to create a European health data space to foster targeted research, diagnosis and treatment, ensure access to safe and top quality digital services in healthcare and pave the way towards a healthier society.



Secure access to citizen’s health data across the EU


A shared EU data infrastructure for precision medicine


Citizens with digital tools for feedback and person-centred care