Objective 1
Align and connect different national Precision Medicine initiatives and Rare Disease repositories, adhering both to the expected security and ethical requirements as well as the relevant national regulations, towards a unified query interface
Objective 2
Specify a reusable protocol and reference implementation for making data models findable, accessible, interoperable and reproducible (FAIR) for humans and machines, aiming to support cross-repository queries and ML through data models rather than data itself
Objective 3
Demonstrate the value and impact of the protocol through an application of a collective ML approach based on combined phenotypic and omics data across repositories, towards higher resolution patient stratification and outcome prediction
Research Centre
University
Research Centre
University
Research centre
Research Centre
University
University
Research Centre
Research Centre
Non profit organization
SME
University
University
University
Research Centre
SME
Machine learning, collective learning, precision medicine, Chronic lymphocytic leukemia, lung cancer, Duchenne muscular dystrophy, Intellectual Disability, privacy-by-design
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