Zobrazeno 1 - 10
of 152
pro vyhledávání: '"Weissmann, Thomas"'
Autor:
Hou, Yihao, Bert, Christoph, Gomaa, Ahmed, Lahmer, Godehard, Hoefler, Daniel, Weissmann, Thomas, Voigt, Raphaela, Schubert, Philipp, Schmitter, Charlotte, Depardon, Alina, Semrau, Sabine, Maier, Andreas, Fietkau, Rainer, Huang, Yixing, Putz, Florian
Generating physician letters is a time-consuming task in daily clinical practice. This study investigates local fine-tuning of large language models (LLMs), specifically LLaMA models, for physician letter generation in a privacy-preserving manner wit
Externí odkaz:
http://arxiv.org/abs/2408.10715
Autor:
Steffen, Ingo G., Weissmann, Thomas, Rothe, Jan Holger, Geisel, Dominik, Chopra, Sascha S., Kahn, Johannes, Hamm, Bernd, Denecke, Timm
The aim of this exploratory study was to evaluate the influence of hepatic steatosis on the detection rate of metastases in gadoxetic acid-enhanced liver magnetic resonance imaging (MRI). A total of 50 patients who underwent gadoxetic acid-enhanced M
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A84786
https://ul.qucosa.de/api/qucosa%3A84786/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A84786/attachment/ATT-0/
Autor:
Gomaa, Ahmed, Huang, Yixing, Hagag, Amr, Schmitter, Charlotte, Höfler, Daniel, Weissmann, Thomas, Breininger, Katharina, Schmidt, Manuel, Stritzelberger, Jenny, Delev, Daniel, Coras, Roland, Dörfler, Arnd, Schnell, Oliver, Frey, Benjamin, Gaipl, Udo S., Semrau, Sabine, Bert, Christoph, Fietkau, Rainer, Putz, Florian
Background: This research aims to improve glioblastoma survival prediction by integrating MR images, clinical and molecular-pathologic data in a transformer-based deep learning model, addressing data heterogeneity and performance generalizability. Me
Externí odkaz:
http://arxiv.org/abs/2405.12963
Autor:
Huang, Yixing, Gomaa, Ahmed, Semrau, Sabine, Haderlein, Marlen, Lettmaier, Sebastian, Weissmann, Thomas, Grigo, Johanna, Tkhayat, Hassen Ben, Frey, Benjamin, Gaipl, Udo S., Distel, Luitpold V., Maier, Andreas, Fietkau, Rainer, Bert, Christoph, Putz, Florian
The potential of large language models in medicine for education and decision making purposes has been demonstrated as they achieve decent scores on medical exams such as the United States Medical Licensing Exam (USMLE) and the MedQA exam. In this wo
Externí odkaz:
http://arxiv.org/abs/2304.11957
Autor:
Putz, Florian, Grigo, Johanna, Weissmann, Thomas, Schubert, Philipp, Hoefler, Daniel, Gomaa, Ahmed, Tkhayat, Hassen Ben, Hagag, Amr, Lettmaier, Sebastian, Frey, Benjamin, Gaipl, Udo S., Distel, Luitpold V., Semrau, Sabine, Bert, Christoph, Fietkau, Rainer, Huang, Yixing
Background: Tumor segmentation in MRI is crucial in radiotherapy (RT) treatment planning for brain tumor patients. Segment anything (SA), a novel promptable foundation model for autosegmentation, has shown high accuracy for multiple segmentation task
Externí odkaz:
http://arxiv.org/abs/2304.07875
Autor:
Kalender, Günay1,2 (AUTHOR) guenay.kalender@vivantes.de, Weissmann, Thomas3 (AUTHOR) thomas.weissmann@uk-erlangne.de, Dinç, Ugur1,3 (AUTHOR) ugur.dinc@vivantes.de
Publikováno v:
Journal of Clinical Medicine. Nov2024, Vol. 13 Issue 21, p6431. 13p.
Autor:
Weissmann, Thomas, Huang, Yixing, Fischer, Stefan, Roesch, Johannes, Mansoorian, Sina, Gaona, Horacio Ayala, Gostian, Antoniu-Oreste, Hecht, Markus, Lettmaier, Sebastian, Deloch, Lisa, Frey, Benjamin, Gaipl, Udo S., Distel, Luitpold V., Maier, Andreas, Iro, Heinrich, Semrau, Sabine, Bert, Christoph, Fietkau, Rainer, Putz, Florian
Publikováno v:
Front. Oncol. 13:1115258
Background: Deep learning (DL)-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still underinvestigated in academic literature. Methods: An expert-delineat
Externí odkaz:
http://arxiv.org/abs/2208.13224
Autor:
Huang, Yixing, Bert, Christoph, Sommer, Philipp, Frey, Benjamin, Gaipl, Udo, Distel, Luitpold V., Weissmann, Thomas, Uder, Michael, Schmidt, Manuel A., Dörfler, Arnd, Maier, Andreas, Fietkau, Rainer, Putz, Florian
Publikováno v:
Medical Physics 2022
Brain metastases occur frequently in patients with metastatic cancer. Early and accurate detection of brain metastases is very essential for treatment planning and prognosis in radiation therapy. To improve brain metastasis detection performance with
Externí odkaz:
http://arxiv.org/abs/2112.11833
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