no code implementations • 14 Mar 2023 • Keno K. Bressem, Jens-Michalis Papaioannou, Paul Grundmann, Florian Borchert, Lisa C. Adams, Leonhard Liu, Felix Busch, Lina Xu, Jan P. Loyen, Stefan M. Niehues, Moritz Augustin, Lennart Grosser, Marcus R. Makowski, Hugo JWL. Aerts, Alexander Löser
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain.
no code implementations • 27 Sep 2022 • Lisa C. Adams, Felix Busch, Daniel Truhn, Marcus R. Makowski, Hugo JWL. Aerts, Keno K. Bressem
Generative models such as DALL-E 2 could represent a promising future tool for image generation, augmentation, and manipulation for artificial intelligence research in radiology provided that these models have sufficient medical domain knowledge.
no code implementations • 24 Oct 2021 • Manuel Schultheiss, Philipp Schmette, Thorsten Sellerer, Rafael Schick, Kirsten Taphorn, Korbinian Mechlem, Lorenz Birnbacher, Bernhard Renger, Marcus R. Makowski, Franz Pfeiffer, Daniela Pfeiffer
Additionally, we predicted the lung thicknesses on the synthetic test set, where the mean-absolute error between the total volumes was 0. 19 liter with a positive correlation (r = 0. 99).
no code implementations • 10 Aug 2021 • Markus Krönke, Christine Eilers, Desislava Dimova, Melanie Köhler, Gabriel Buschner, Lilit Mirzojan, Lemonia Konstantinidou, Marcus R. Makowski, James Nagarajah, Nassir Navab, Wolfgang Weber, Thomas Wendler
Conclusion: Tracked 3D ultrasound combined with a CNN segmentation significantly reduces interobserver variability in thyroid volumetry and increases the accuracy of the measurements with shorter acquisition times.
no code implementations • 30 Jul 2021 • Moritz Knolle, Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
The application of differential privacy to the training of deep neural networks holds the promise of allowing large-scale (decentralized) use of sensitive data while providing rigorous privacy guarantees to the individual.
no code implementations • 29 Jul 2021 • Matthias Keicher, Hendrik Burwinkel, David Bani-Harouni, Magdalini Paschali, Tobias Czempiel, Egon Burian, Marcus R. Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler
Specifically, we introduce a multimodal similarity metric to build a population graph for clustering patients and an image-based end-to-end Graph Attention Network to process this graph and predict the COVID-19 patient outcomes: admission to ICU, need for ventilation and mortality.
no code implementations • 9 Jul 2021 • Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
We show that differentially private stochastic gradient descent (DP-SGD) can yield poorly calibrated, overconfident deep learning models.
no code implementations • 25 Jan 2021 • Keno K. Bressem, Stefan M. Niehues, Bernd Hamm, Marcus R. Makowski, Janis L. Vahldiek, Lisa C. Adams
Our model performed comparable to previously published 3D U-Net architectures, achieving a mean Dice score of 0. 679 on the tuning dataset, 0. 648 on the Coronacases dataset and 0. 405 on the MosMed dataset.