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There are several videos of our chair on this page. More on our Youtube channel.
Talks
Research at i5
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Multimodal Immersive Learning with AI (Michal Slupczynski)
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Semantic Web in Action (Johannes Theissen-Lipp)
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PADME Pitch
PADME (Platform for Analysis and Distributed Machine Learning for Enterprises) 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.
Relevant publications:
https://www.thieme-connect.de/products/ejournals/abstract/10.1055/s-0041-1740564
https://direct.mit.edu/dint/article/3/4/528/101036/DAMS-A-Distributed-Analytics-Metadata-Schema
More information and contact:
https://dbis.rwth-aachen.de/dbis/index.php/user/welten/