In-context learning enables multimodal large language models to classify cancer pathology images. - Dyke Ferber; Georg Wölflein; Isabella C. Wiest; Marta Ligero; Srividhya Sainath; Narmin Ghaffari Laleh; Omar S. M. El Nahhas; Gustav Müller-Franzes; Dirk Jäger; Daniel Truhn; Jakob Nikolas Kather (CoRR, 2024)

Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology. - Dyke Ferber; Omar S. M. El Nahhas; Georg Wölflein; Isabella C. Wiest; Jan Clusmann; Marie-Elisabeth Leßman; Sebastian Foersch; Jacqueline Lammert; Maximilian Tschochohei; Dirk Jäger; Manuel Salto-Tellez; Nikolaus Schultz; et al. (CoRR, 2024)

End-To-End Clinical Trial Matching with Large Language Models. - Dyke Ferber; Lars Hilgers; Isabella C. Wiest; Marie-Elisabeth Leßmann; Jan Clusmann; Peter Neidlinger; Jiefu Zhu; Georg Wölflein; Jacqueline Lammert; Maximilian Tschochohei; Heiko Böhme; Dirk Jäger; et al. (CoRR, 2024)

Prompt Injection Attacks on Large Language Models in Oncology. - Jan Clusmann; Dyke Ferber; Isabella C. Wiest; Carolin V. Schneider; Titus J. Brinker; Sebastian Foersch; Daniel Truhn; Jakob Nikolas Kather (CoRR, 2024)

Privacy-preserving large language models for structured medical information retrieval. - Isabella C. Wiest; Dyke Ferber; Jiefu Zhu; Marko van Treeck; Sonja K. Meyer; Radhika Juglan; Zunamys I. Carrero; Daniel Paech; Jens Kleesiek; Matthias P. Ebert; Daniel Truhn; Jakob Nikolas Kather (npj Digit. Medicine, 2024)

How machine learning on real world clinical data improves adverse event recording for endoscopy. - Stefan Wittlinger; Isabella C. Wiest; Mahboubeh Jannesari Ladani; Jakob Nikolas Kather; Matthias P. Ebert; Fabian Siegel; Sebastian Belle (npj Digit. Medicine, 2025)