Julian O. Matschinske

According to our database, Julian O. Matschinske authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Privacy-Preserving Multi-Center Differential Protein Abundance Analysis with FedProt.

Yuliya Burankova, Miriam Abele, Mohammad Bakhtiari, Christine von Törne, Teresa Barth, Lisa Schweizer, Pieter Giesbertz, Johannes R. Schmidt, Stefan Kalkhof, Janina Müller-Deile, Peter A. van Veelen, Yassene Mohammed, Elke Hammer, Lis Arend, Klaudia Adamowicz, Tanja Laske, Anne Hartebrodt, Tobias Frisch, Chen Meng, Julian O. Matschinske, Julian Späth, Richard Röttger, Veit Schwämmle, Stefanie M. Hauck, Stefan Lichtenthaler, Axel Imhof, Matthias Mann, Christina Ludwig, Bernhard Küster, Jan Baumbach, Olga I. Zolotareva

CoRR, 2024

2023

Privacy-aware Artificial Intelligence in Systems Medicine

Julian O. Matschinske

PhD thesis, 2023

2022

dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning.

Han Cao, Youcheng Zhang, Jan Baumbach, Paul R. Burton, Dominic B. Dwyer, Nikolaos Koutsouleris, Julian O. Matschinske, Yannick Marcon, Sivanesan Rajan, Thilo Rieg, Patricia Ryser-Welch, Julian Späth, Carl Herrmann, Emanuel Schwarz

Bioinform., October, 2022

Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare - a proof of concept study for the prediction of coronary artery calcification scores.

Justus Wolff, Julian O. Matschinske, Dietrich Baumgart, Anne Pytlik, Andreas Keck, Arunakiry Natarajan, Claudio E. von Schacky, Josch Pauling, Jan Baumbach

J. Integr. Bioinform., 2022

Federated Random Forests can improve local performance of predictive models for various healthcare applications.

Anne-Christin Hauschild, Marta Lemanczyk, Julian O. Matschinske, Tobias Frisch, Olga I. Zolotareva, Andreas Holzinger, Jan Baumbach, Dominik Heider

Bioinform., 2022

2021

Lessons from the COVID-19 pandemic for advancing computational drug repurposing strategies.

Gihanna Galindez, Julian O. Matschinske, Tim D. Rose, Sepideh Sadegh, Marisol Salgado-Albarrán, Julian Späth, Jan Baumbach, Josch Konstantin Pauling

Nat. Comput. Sci., 2021

HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning.

Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Julian O. Matschinske, Jan Baumbach, Daniel Rueckert, Georgios Kaissis

CoRR, 2021

The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond.

Julian O. Matschinske, Julian Späth, Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Anne Hartebrodt, Balázs Orbán, Sándor Fejér, Olga I. Zolotareva, Mohammad Bakhtiari, Béla Bihari, Marcus D. Bloice, Nina C. Donner, Walid Fdhila, Tobias Frisch, Anne-Christin Hauschild, Dominik Heider, Andreas Holzinger, Walter Hötzendorfer, Jan Hospes, Tim Kacprowski, Markus Kastelitz, Markus List, Rudolf Mayer, Mónika Moga, Heimo Müller, Anastasia Pustozerova, Richard Röttger, Anna Saranti, Harald H. H. W. Schmidt, Christof Tschohl, Nina Kerstin Wenke, Jan Baumbach

CoRR, 2021

Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.

Franziska Hufsky, Kevin Lamkiewicz, Alexandre Almeida, Abdel Aouacheria, Cecilia N. Arighi, Alex Bateman, Jan Baumbach, Niko Beerenwinkel, Christian Brandt, Marco Cacciabue, Sara Chuguransky, Oliver Drechsel, Robert D. Finn, Adrian Fritz, Stephan Fuchs, Georges Hattab, Anne-Christin Hauschild, Dominik Heider, Marie Hoffmann, Martin Hölzer, Stefan Hoops, Lars Kaderali, Ioanna Kalvari, Max von Kleist, Renó Kmiecinski, Denise Kühnert, Gorka Lasso, Pieter Libin, Markus List, Hannah F. Löchel, Maria Jesus Martin, Roman Martin, Julian O. Matschinske, Alice C. McHardy, Pedro Mendes, Jaina Mistry, Vincent Navratil, Eric P. Nawrocki, Áine Niamh O'toole, Nancy Ontiveros-Palacios, Anton I. Petrov, Guillermo Rangel-Pineros, Nicole Redaschi, Susanne Reimering, Knut Reinert, Alejandro Reyes, Lorna J. Richardson, David L. Robertson, Sepideh Sadegh, Joshua B. Singer, Kristof Theys, Chris Upton, Marius Welzel, Lowri Williams, Manja Marz

Briefings Bioinform., 2021

2020

Privacy-preserving Artificial Intelligence Techniques in Biomedicine.

Reihaneh Torkzadehmahani, Reza Nasirigerdeh, David B. Blumenthal, Tim Kacprowski, Markus List, Julian O. Matschinske, Julian Späth, Nina Kerstin Wenke, Béla Bihari, Tobias Frisch, Anne Hartebrodt, Anne-Christin Hauschild, Dominik Heider, Andreas Holzinger, Walter Hötzendorfer, Markus Kastelitz, Rudolf Mayer, Cristian Nogales, Anastasia Pustozerova, Richard Röttger, Harald H. H. W. Schmidt, Ameli Schwalber, Christof Tschohl, Andrea Wohner, Jan Baumbach

CoRR, 2020

2019

Query-Driven Data Minimization with the DataEconomist.

Peter K. Schwab, Julian O. Matschinske, Andreas M. Wahl, Klaus Meyer-Wegener

Proceedings of the Advances in Database Technology, 2019

2018

Towards Query-Driven Data Minimization.

Peter K. Schwab, Julian O. Matschinske, Andreas M. Wahl, Klaus Meyer-Wegener

Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", 2018