Zobrazeno 1 - 10
of 680
pro vyhledávání: '"Makowski, Marcus R"'
Autor:
Dorfner, Felix J., Dada, Amin, Busch, Felix, Makowski, Marcus R., Han, Tianyu, Truhn, Daniel, Kleesiek, Jens, Sushil, Madhumita, Lammert, Jacqueline, Adams, Lisa C., Bressem, Keno K.
Large language models (LLMs) have shown potential in biomedical applications, leading to efforts to fine-tune them on domain-specific data. However, the effectiveness of this approach remains unclear. This study evaluates the performance of biomedica
Externí odkaz:
http://arxiv.org/abs/2408.13833
Autor:
Kaster, Lennard, Klein, Henriette, Marka, Alexander W., Urban, Theresa, Karl, Sandra, Gassert, Florian T., Steinhelfer, Lisa, Makowski, Marcus R., Pfeiffer, Daniela, Pfeiffer, Franz
Objectives: Evaluating the effects and artifacts introduced by medical foreign bodies in clinical dark-field chest radiographs and assessing their influence on the evaluation of pulmonary tissue, compared to conventional radiographs. Material & Metho
Externí odkaz:
http://arxiv.org/abs/2408.10855
Autor:
Dorfner, Felix J., Vahldiek, Janis L., Donle, Leonhard, Zhukov, Andrei, Xu, Lina, Häntze, Hartmut, Makowski, Marcus R., Aerts, Hugo J. W. L., Proft, Fabian, Rodriguez, Valeria Rios, Rademacher, Judith, Protopopov, Mikhail, Haibel, Hildrun, Diekhoff, Torsten, Torgutalp, Murat, Adams, Lisa C., Poddubnyy, Denis, Bressem, Keno K.
Purpose: To examine whether incorporating anatomical awareness into a deep learning model can improve generalizability and enable prediction of disease progression. Methods: This retrospective multicenter study included conventional pelvic radiograph
Externí odkaz:
http://arxiv.org/abs/2405.07369
Autor:
Bressem, Keno K., Papaioannou, Jens-Michalis, Grundmann, Paul, Borchert, Florian, Adams, Lisa C., Liu, Leonhard, Busch, Felix, Xu, Lina, Loyen, Jan P., Niehues, Stefan M., Augustin, Moritz, Grosser, Lennart, Makowski, Marcus R., Aerts, Hugo JWL., Löser, Alexander
Publikováno v:
Expert Systems with Applications 2024;237(21):121598
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million German medical documents and has been shown to achieve new state-of-the-ar
Externí odkaz:
http://arxiv.org/abs/2303.08179
Autor:
Adams, Lisa C., Busch, Felix, Truhn, Daniel, Makowski, Marcus R., Aerts, Hugo JWL., Bressem, Keno K.
Publikováno v:
J Med Internet Res 2023;25:e43110
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. Her
Externí odkaz:
http://arxiv.org/abs/2209.13696
Autor:
Ebrahimi Ardjomand, Saba, Meurer, Felix, Ehmann, Yannick, Pogorzelski, Jonas, Waschulzik, Birgit, Makowski, Marcus R., Siebenlist, Sebastian, Heuck, Andreas, Woertler, Klaus, Neumann, Jan
Publikováno v:
In Academic Radiology August 2024 31(8):3327-3335
Autor:
Bayerl, Christian, Safraou, Yasmine, Reiter, Rolf, Proß, Vanessa, Lehmann, Kai, Kühl, Anja A., Shahryari, Mehrgan, Hamm, Bernd, Sack, Ingolf, Makowski, Marcus R., Braun, Jürgen, Asbach, Patrick
Publikováno v:
In Journal of the Mechanical Behavior of Biomedical Materials December 2024 160
Autor:
Krönke, Markus, Eilers, Christine, Dimova, Desislava, Köhler, Melanie, Buschner, Gabriel, Mirzojan, Lilit, Konstantinidou, Lemonia, Makowski, Marcus R., Nagarajah, James, Navab, Nassir, Weber, Wolfgang, Wendler, Thomas
Background: Thyroid volumetry is crucial in diagnosis, treatment and monitoring of thyroid diseases. However, conventional thyroid volumetry with 2D ultrasound is highly operator-dependent. This study compares 2D ultrasound and tracked 3D ultrasound
Externí odkaz:
http://arxiv.org/abs/2108.10118
Autor:
Kader, Avan, Snellings, Joachim, Adams, Lisa C., Gottheil, Pablo, Mangarova, Dilyana B., Heyl, Jennifer L., Kaufmann, Jan O., Moeckel, Jana, Brangsch, Julia, Auer, Timo A., Collettini, Federico, Sauer, Frank, Hamm, Bernd, Käs, Josef, Sack, Ingolf, Makowski, Marcus R., Braun, Jürgen
Publikováno v:
In Biomaterials Advances July 2024 161
Autor:
Knolle, Moritz, Usynin, Dmitrii, Ziller, Alexander, Makowski, Marcus R., Rueckert, Daniel, Kaissis, Georgios
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. The predominant approach to
Externí odkaz:
http://arxiv.org/abs/2107.14582