Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Ferber, Dyke"'
Autor:
Lammert, Jacqueline, Pfarr, Nicole, Kuligin, Leonid, Mathes, Sonja, Dreyer, Tobias, Modersohn, Luise, Metzger, Patrick, Ferber, Dyke, Kather, Jakob Nikolas, Truhn, Daniel, Adams, Lisa Christine, Bressem, Keno Kyrill, Lange, Sebastian, Schwamborn, Kristina, Boeker, Martin, Kiechle, Marion, Schatz, Ulrich A., Bronger, Holger, Tschochohei, Maximilian
Rare gynecological tumors (RGTs) present major clinical challenges due to their low incidence and heterogeneity. The lack of clear guidelines leads to suboptimal management and poor prognosis. Molecular tumor boards accelerate access to effective the
Externí odkaz:
http://arxiv.org/abs/2409.00544
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:
Arasteh, Soroosh Tayebi, Lotfinia, Mahshad, Bressem, Keno, Siepmann, Robert, Ferber, Dyke, Kuhl, Christiane, Kather, Jakob Nikolas, Nebelung, Sven, Truhn, Daniel
Large language models (LLMs) have advanced the field of artificial intelligence (AI) in medicine. However LLMs often generate outdated or inaccurate information based on static training datasets. Retrieval augmented generation (RAG) mitigates this by
Externí odkaz:
http://arxiv.org/abs/2407.15621
Autor:
Ferber, Dyke, Hilgers, Lars, Wiest, Isabella C., Leßmann, Marie-Elisabeth, Clusmann, Jan, Neidlinger, Peter, Zhu, Jiefu, Wölflein, Georg, Lammert, Jacqueline, Tschochohei, Maximilian, Böhme, Heiko, Jäger, Dirk, Aldea, Mihaela, Truhn, Daniel, Höper, Christiane, Kather, Jakob Nikolas
Matching cancer patients to clinical trials is essential for advancing treatment and patient care. However, the inconsistent format of medical free text documents and complex trial eligibility criteria make this process extremely challenging and time
Externí odkaz:
http://arxiv.org/abs/2407.13463
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:
Ferber, Dyke, Wölflein, Georg, Wiest, Isabella C., Ligero, Marta, Sainath, Srividhya, Laleh, Narmin Ghaffari, Nahhas, Omar S. M. El, Müller-Franzes, Gustav, Jäger, Dirk, Truhn, Daniel, Kather, Jakob Nikolas
Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. However, this process is computationally and technically demanding. In language processin
Externí odkaz:
http://arxiv.org/abs/2403.07407
Autor:
Wölflein, Georg, Ferber, Dyke, Meneghetti, Asier R., Nahhas, Omar S. M. El, Truhn, Daniel, Carrero, Zunamys I., Harrison, David J., Arandjelović, Ognjen, Kather, Jakob Nikolas
Weakly supervised whole slide image classification is a key task in computational pathology, which involves predicting a slide-level label from a set of image patches constituting the slide. Constructing models to solve this task involves multiple de
Externí odkaz:
http://arxiv.org/abs/2311.11772
Autor:
Wiest, Isabella C., Ferber, Dyke, Wittlinger, Stefan, Ebert, Matthias P., Belle, Sebastian, Kather, Jakob Nikolas
Publikováno v:
In iGIE August 2024
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Akademický článek
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