Zobrazeno 1 - 10
of 4 490
pro vyhledávání: '"Semrau A"'
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:
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:
Jarmolovičius, Mindaugas, Semrau, Daniel, Buglia, Henrique, Shevchenko, Mykyta, Ferreira, Filipe M., Sillekens, Eric, Bayvel, Polina, Killey, Robert I.
We model the transmission of ultrawideband signals, including wavelength-dependent fibre parameters: dispersion, nonlinear coefficient and effective fibre core area. To that end, the inter-channel stimulated Raman scattering Gaussian noise integral m
Externí odkaz:
http://arxiv.org/abs/2401.18022
One of the main goals of developmental biology is to reveal the gene regulatory networks (GRNs) underlying the robust differentiation of multipotent progenitors into precisely specified cell types. Most existing methods to infer GRNs from experimenta
Externí odkaz:
http://arxiv.org/abs/2401.07379
Autor:
Maya Semrau, Petra C. Gronholm, Julian Eaton, Pallab K. Maulik, Bethel Ayele, Ioannis Bakolis, Gurucharan Bhaskar Mendon, Kalpana Bhattarai, Elaine Brohan, Anish V. Cherian, Mercian Daniel, Eshetu Girma, Dristy Gurung, Ariam Hailemariam, Charlotte Hanlon, Andy Healey, Sudha Kallakuri, Jie Li, Santosh Loganathan, Ning Ma, Yurong Ma, Amani Metsahel, Uta Ouali, Nahel Yaziji, Yosra Zgueb, Wufang Zhang, Xiaotong Zhang, Graham Thornicroft, Nicole Votruba
Publikováno v:
International Journal of Mental Health Systems, Vol 18, Iss 1, Pp 1-16 (2024)
Abstract Background Stigma and discrimination towards people with mental health conditions by their communities are common worldwide. This can result in a range of negative outcomes for affected persons, including poor access to health care. However,
Externí odkaz:
https://doaj.org/article/eeab02888fcd4d3d826567218b2a9734
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-5 (2024)
Abstract Methane is a potent but relatively short-lived greenhouse gas, with anthropogenic and natural sources and rapidly increasing atmospheric concentrations. Hence, it is an important target for reducing emissions and increasing sinks, as doing s
Externí odkaz:
https://doaj.org/article/f8969bb8d8d040f6843b3adc950c1054
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
Publikováno v:
Frontiers in Health Services, Vol 4 (2024)
Externí odkaz:
https://doaj.org/article/34a74ed0426a4ba29e6938aa6deba129
Autor:
Semrau, Maya1 m.semrau@bsms.ac.uk, Gronholm, Petra C.2,3, Eaton, Julian4,5, Maulik, Pallab K.6,7,8, Ayele, Bethel9, Bakolis, Ioannis3,10, Mendon, Gurucharan Bhaskar11, Bhattarai, Kalpana12, Brohan, Elaine2, Cherian, Anish V.11, Daniel, Mercian6, Girma, Eshetu9, Gurung, Dristy3,12, Hailemariam, Ariam9, Hanlon, Charlotte2,13, Healey, Andy14, Kallakuri, Sudha6, Li, Jie15, Loganathan, Santosh16, Ma, Ning17
Publikováno v:
International Journal of Mental Health Systems. 11/18/2024, Vol. 18 Issue 1, p1-16. 16p.