no code implementations • 25 Aug 2024 • Felix J. Dorfner, Amin Dada, Felix Busch, Marcus R. Makowski, Tianyu Han, Daniel Truhn, Jens Kleesiek, Madhumita Sushil, Jacqueline Lammert, Lisa C. Adams, Keno K. Bressem
Large language models (LLMs) have shown potential in biomedical applications, leading to efforts to fine-tune them on domain-specific data.
1 code implementation • 12 May 2024 • Felix J. Dorfner, Janis L. Vahldiek, Leonhard Donle, Andrei Zhukov, Lina Xu, Hartmut Häntze, Marcus R. Makowski, Hugo J. W. L. Aerts, Fabian Proft, Valeria Rios Rodriguez, Judith Rademacher, Mikhail Protopopov, Hildrun Haibel, Torsten Diekhoff, Murat Torgutalp, Lisa C. Adams, Denis Poddubnyy, Keno K. Bressem
For the second cohort, follow-up data of 311 patients was used to examine progression prediction capabilities.
1 code implementation • 10 May 2024 • Hartmut Häntze, Lina Xu, Christian J. Mertens, Felix J. Dorfner, Leonhard Donle, Felix Busch, Avan Kader, Sebastian Ziegelmayer, Nadine Bayerl, Nassir Navab, Daniel Rueckert, Julia Schnabel, Hugo JWL Aerts, Daniel Truhn, Fabian Bamberg, Jakob Weiß, Christopher L. Schlett, Steffen Ringhof, Thoralf Niendorf, Tobias Pischon, Hans-Ulrich Kauczor, Tobias Nonnenmacher, Thomas Kröncke, Henry Völzke, Jeanette Schulz-Menger, Klaus Maier-Hein, Mathias Prokop, Bram van Ginneken, Alessa Hering, Marcus R. Makowski, Lisa C. Adams, Keno K. Bressem
A human-in-the-loop annotation workflow was employed, leveraging cross-modality transfer learning from an existing CT segmentation model to segment 40 anatomical structures.
no code implementations • 4 May 2024 • Hartmut Häntze, Lina Xu, Maximilian Rattunde, Leonhard Donle, Felix J. Dorfner, Alessa Hering, Lisa C. Adams, Keno K. Bressem
In this study, we show that a simple image inversion technique can significantly improve the segmentation quality of CT segmentation models on MRI data.
no code implementations • 19 Feb 2024 • Felix J. Dorfner, Liv Jürgensen, Leonhard Donle, Fares Al Mohamad, Tobias R. Bodenmann, Mason C. Cleveland, Felix Busch, Lisa C. Adams, James Sato, Thomas Schultz, Albert E. Kim, Jameson Merkow, Keno K. Bressem, Christopher P. Bridge
While recent publications have explored GPT-4 in its application to extracting information of interest from radiology reports, there has not been a real-world comparison of GPT-4 to different leading open-source models.
1 code implementation • 29 Sep 2023 • Tianyu Han, Sven Nebelung, Firas Khader, Tianci Wang, Gustav Mueller-Franzes, Christiane Kuhl, Sebastian Försch, Jens Kleesiek, Christoph Haarburger, Keno K. Bressem, Jakob Nikolas Kather, Daniel Truhn
We validate our findings in a set of 1, 038 incorrect biomedical facts.
no code implementations • 14 Apr 2023 • Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, Paul Grundmann, Tom Oberhauser, Alexander Löser, Daniel Truhn, Keno K. Bressem
As large language models (LLMs) like OpenAI's GPT series continue to make strides, we witness the emergence of artificial intelligence applications in an ever-expanding range of fields.
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 • 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.
no code implementations • 20 Feb 2020 • Keno K. Bressem, Lisa Adams, Christoph Erxleben, Bernd Hamm, Stefan Niehues, Janis Vahldiek
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research.