Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Försch, Sebastian"'
Autor:
Neidlinger, Peter, Nahhas, Omar S. M. El, Muti, Hannah Sophie, Lenz, Tim, Hoffmeister, Michael, Brenner, Hermann, van Treeck, Marko, Langer, Rupert, Dislich, Bastian, Behrens, Hans Michael, Röcken, Christoph, Foersch, Sebastian, Truhn, Daniel, Marra, Antonio, Saldanha, Oliver Lester, Kather, Jakob Nikolas
Advancements in artificial intelligence have driven the development of numerous pathology foundation models capable of extracting clinically relevant information. However, there is currently limited literature independently evaluating these foundatio
Externí odkaz:
http://arxiv.org/abs/2408.15823
Autor:
Clusmann, Jan, Ferber, Dyke, Wiest, Isabella C., Schneider, Carolin V., Brinker, Titus J., Foersch, Sebastian, Truhn, Daniel, Kather, Jakob N.
Vision-language artificial intelligence models (VLMs) possess medical knowledge and can be employed in healthcare in numerous ways, including as image interpreters, virtual scribes, and general decision support systems. However, here, we demonstrate
Externí odkaz:
http://arxiv.org/abs/2407.18981
Autor:
Ferber, Dyke, Nahhas, Omar S. M. El, Wölflein, Georg, Wiest, Isabella C., Clusmann, Jan, Leßman, Marie-Elisabeth, Foersch, Sebastian, Lammert, Jacqueline, Tschochohei, Maximilian, Jäger, Dirk, Salto-Tellez, Manuel, Schultz, Nikolaus, Truhn, Daniel, Kather, Jakob Nikolas
Multimodal artificial intelligence (AI) systems have the potential to enhance clinical decision-making by interpreting various types of medical data. However, the effectiveness of these models across all medical fields is uncertain. Each discipline p
Externí odkaz:
http://arxiv.org/abs/2404.04667
Autor:
Dar, Salman Ul Hassan, Seyfarth, Marvin, Kahmann, Jannik, Ayx, Isabelle, Papavassiliu, Theano, Schoenberg, Stefan O., Frey, Norbert, Baeßler, Bettina, Foersch, Sebastian, Truhn, Daniel, Kather, Jakob Nikolas, Engelhardt, Sandy
AI models present a wide range of applications in the field of medicine. However, achieving optimal performance requires access to extensive healthcare data, which is often not readily available. Furthermore, the imperative to preserve patient privac
Externí odkaz:
http://arxiv.org/abs/2402.01054
Autor:
Nahhas, Omar S. M. El, van Treeck, Marko, Wölflein, Georg, Unger, Michaela, Ligero, Marta, Lenz, Tim, Wagner, Sophia J., Hewitt, Katherine J., Khader, Firas, Foersch, Sebastian, Truhn, Daniel, Kather, Jakob Nikolas
Hematoxylin- and eosin (H&E) stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-based methods in computational pathology enabled the prediction of biomarkers directly from WSIs.
Externí odkaz:
http://arxiv.org/abs/2312.10944
Autor:
Han, Tianyu, Nebelung, Sven, Khader, Firas, Wang, Tianci, Mueller-Franzes, Gustav, Kuhl, Christiane, Försch, Sebastian, Kleesiek, Jens, Haarburger, Christoph, Bressem, Keno K., Kather, Jakob Nikolas, Truhn, Daniel
Large language models (LLMs) have broad medical knowledge and can reason about medical information across many domains, holding promising potential for diverse medical applications in the near future. In this study, we demonstrate a concerning vulner
Externí odkaz:
http://arxiv.org/abs/2309.17007
Autor:
Khader, Firas, Mueller-Franzes, Gustav, Arasteh, Soroosh Tayebi, Han, Tianyu, Haarburger, Christoph, Schulze-Hagen, Maximilian, Schad, Philipp, Engelhardt, Sandy, Baessler, Bettina, Foersch, Sebastian, Stegmaier, Johannes, Kuhl, Christiane, Nebelung, Sven, Kather, Jakob Nikolas, Truhn, Daniel
Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models in particular have generated realistic images from textual input, as demonstrated by DALL-E 2, Imagen and Stable Diffusion. However, t
Externí odkaz:
http://arxiv.org/abs/2211.03364
Autor:
Jurmeister, Philipp, Leitheiser, Maximilian, Arnold, Alexander, Capilla, Emma Payá, Mochmann, Liliana H., Zhdanovic, Yauheniya, Schleich, Konstanze, Jung, Nina, Chimal, Edgar Calderon, Jung, Andreas, Kumbrink, Jörg, Harter, Patrick, Prenißl, Niklas, Elezkurtaj, Sefer, Brcic, Luka, Deigendesch, Nikolaus, Frank, Stephan, Hench, Jürgen, Försch, Sebastian, Breimer, Gerben, van Engen van Grunsven, Ilse, Lassche, Gerben, van Herpen, Carla, Zhou, Fang, Snuderl, Matija, Agaimy, Abbas, Müller, Klaus-Robert, von Deimling, Andreas, Capper, David, Klauschen, Frederick, Ihrler, Stephan
Publikováno v:
In Modern Pathology December 2024 37(12)
Autor:
Grass, Albert, Kasajima, Atsuko, Foersch, Sebastian, Kriegsmann, Mark, Brobeil, Alexander, Schmitt, Maxime, Wagner, Daniel, Poppinga, Jelte, Wiese, Dominik, Maurer, Elisabeth, Kirschbaum, Andreas, Muley, Thomas, Winter, Hauke, Rinke, Anja, Gress, Thomas M., Kremer, Markus, Evert, Matthias, Märkl, Bruno, Quaas, Alexander, Eckstein, Markus, Tschurtschenthaler, Markus, Klöppel, Günter, Denkert, Carsten, Bartsch, Detlef K., Jesinghaus, Moritz
Publikováno v:
In Modern Pathology April 2024 37(4)
Autor:
Truhn, Daniel, Tayebi Arasteh, Soroosh, Saldanha, Oliver Lester, Müller-Franzes, Gustav, Khader, Firas, Quirke, Philip, West, Nicholas P., Gray, Richard, Hutchins, Gordon G.A., James, Jacqueline A., Loughrey, Maurice B., Salto-Tellez, Manuel, Brenner, Hermann, Brobeil, Alexander, Yuan, Tanwei, Chang-Claude, Jenny, Hoffmeister, Michael, Foersch, Sebastian, Han, Tianyu, Keil, Sebastian, Schulze-Hagen, Maximilian, Isfort, Peter, Bruners, Philipp, Kaissis, Georgios, Kuhl, Christiane, Nebelung, Sven, Kather, Jakob Nikolas
Publikováno v:
In Medical Image Analysis February 2024 92