Dyke Ferber

According to our database, Dyke Ferber authored at least 8 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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

Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors.

Jacqueline Lammert, Nicole Pfarr, Leonid Kuligin, Sonja Mathes, Tobias Dreyer, Luise Modersohn, Patrick Metzger, Dyke Ferber, Jakob Nikolas Kather, Daniel Truhn, Lisa Christine Adams, Keno K. Bressem, Sebastian Lange, Kristina Schwamborn, Martin Boeker, Marion Kiechle, Ulrich A. Schatz, Holger Bronger, Maximilian Tschochohei

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

RadioRAG: Factual Large Language Models for Enhanced Diagnostics in Radiology Using Dynamic Retrieval Augmented Generation.

Soroosh Tayebi Arasteh, Mahshad Lotfinia, Keno K. Bressem, Robert Siepmann, Dyke Ferber, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn

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, Mihaela Aldea, Daniel Truhn, Christiane Höper, 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, Daniel Truhn, Jakob Nikolas Kather

CoRR, 2024

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

2023

A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology.

Georg Wölflein, Dyke Ferber, Asier Rabasco Meneghetti, Omar S. M. El Nahhas, Daniel Truhn, Zunamys I. Carrero, David J. Harrison, Ognjen Arandjelovic, Jakob Nikolas Kather

CoRR, 2023