Welcome to PADME

Platform for Analytics and Distributed Machine Learning for Enterprises

PADME is a Distributed Analytics (DA) infrastructure that brings the algorithms to the data instead of vice versa. By following this paradigm shift, it proposes a solution for persistent privacy-related challenges. It is developed in compliance with Personal Health Train(PHT) approach. It provides a generic solution not limited to the health domain but any domain that need to analyze distributed data.

PHT is a novel approach, aiming to establish a distributed data analytics infrastructure enabling the (re)use of distributed healthcare data, while data owners stay in control of their data. The main principle of the PHT is that data remains in its original location, and analytical tasks visit data sources and execute the tasks. The PHT provides a distributed, flexible approach to use data in a network of participants, incorporating the FAIR principles.

Our study is part of German MII and GoFAIR initiatives.

Recent News

Accepted paper for Methods of Information in Medicine journal
By sascha welten / January 17, 2022

Accepted paper for Methods of Information in Medicine journal

Our paper A Privacy-Preserving Distributed Analytics Platform for Health Care Data will be published in the Methods of Information in...

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By sascha welten / October 13, 2021

Prof. Beyan at Digital Health Europe Summit

Prof. Beyan attended a panel on Distributed Analytics at the Digital Health Europe Summit . During this panel, experts discussed...

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By sascha welten / October 7, 2021

Exploring new Domains

For the next 12 months, we are exploring the applicability of PADME in an other domain beyond healthcare. As part...

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Station Registry online!
By sascha welten / September 3, 2021

Station Registry online!

We are happy to announce that we successfully linked our PADME ecosystem with the Station Registry from our partners in...

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Accepted paper at PDFL workshop 2021
By yongli mou / August 18, 2021

Accepted paper at PDFL workshop 2021

Our paper Optimized Federated Learning on Class-biased Distributed Data Sources is accepted for presentation at the PDFL workshop 2021 in...

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Accepted paper for Data Intelligence journal
By sascha welten / May 10, 2021

Accepted paper for Data Intelligence journal

Our paper DAMS: A Distributed Analytics Metadata Schema will be published in the Data Intelligence journal.

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Accepted Paper at MIE21
By sascha welten / May 5, 2021

Accepted Paper at MIE21

Our paper Distributed Skin Lesion Analysis across Decentralised Data Sources has been accepted for MIE21.

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Re-deploy of PADME Central Service was successful
By sascha welten / April 30, 2021

Re-deploy of PADME Central Service was successful

The growth of our infrastructure forced us to re-structure our central server. All services are now accessible via our new...

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