paroma-med-v1-numbers

AN EU FUNDED PROJECT

Learn more about PAROMA-MED project, here is the flyer!

Privacy Aware and Privacy Preserving Distributed and Robust Machine Learning for Medical Applications

Machine learning can lead to great advancements with respect to digital services and applications in the field of medical sector, the training process based on real medical patient data is blocked by the fact that uncontrolled access to and exposure of such assets is not allowed by data protection legislation. The EU-funded PAROMA-MED project aims to develop novel technologies, tools, services and architectures for patients, health professionals, data scientists and health domain businesses so that they will be able to interact in the context of data and ML federations according to legal constraints and with complete respect to data owners’ rights from privacy protection to fine grained governance, without performance and functionality penalties of ML/AI workflows and applications.

PAROMA-MED Presents at Easinet

On 10th March PAROMA-MED’s Technical Manager Kostas Koutsopoulos (Qualtek SRL) presented how PAROMA-MED ideas have been consolidated into a realistic value proposition of what the project has defined as “Functional […] 
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PAROMA-MED at SCC 2025

From 10-13th March, the project PAROMA-MED showcased its platform and demonstrated its solutions via a booth at the 14th International ITG Conference on Systems, Communications and Coding (SCC), hosted at […] 
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PAROMA-MED 10th Plenary Meeting: A Key Step Toward Project Completion

The 10th Plenary Meeting of the PAROMA-MED project took place from February 18 to 19 in Athens, Greece, hosted at the prestigious Stavros Niarchos Foundation Cultural Center. Organized by the […] 
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PAROMA-MED & TRANSCEND Joint Workshop

  On 29th January, the project PAROMA-MED showcased its platform and demonstrated its solutions in a collaborative workshop with the project TRANSCEND. The joint workshop organized by PAROMA-MED and TRANSCEND […] 
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All you need to know about Pybiscus

Pybiscus, a pioneering open-source tool developed within the PAROMA-MED project, offers an innovative approach to Federated Learning (FL). Available on GitHub: https://github.com/ThalesGroup/pybiscus   Here are six key points to understand […] 
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Paper Presentation at IEEE GLOBECOM 2024

The PAROMA-MED project proudly announces the publication of the groundbreaking paper titled “6G Sustainable Privacy Preserving Framework Enabling Federated Learning for Health Data” by Anastasius Gavras, Programme Manager at Eurescom […] 
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