Jonah Bosserhoff

Student Assistant

Real World Data & Explainable AI

Institute for AI in Medicine, Germany

Publications

2026

An explainable transformer model learning from entire treatment timelines for pan-cancer risk profiling across healthcare systems Philipp Keyl, Niklas Kiermeyer, Jonah Bosserhoff, Tim Lenfers, Thibault Niederhauser, Bowen Fan, Thomas Schnake, Simon Schallenberg, Fabio Aubele, Solveig Kuss, Mina Jamshidi Idaji, Philipp Jurmeister, Moon Kim, Sebastian Bauer, Nikolaos Bechrakis, Michael Forsting, Dagmar Führer-Sakel, Martin Glas, Viktor Grünwald, Boris Hadaschik, Ken Herrmann, Stefan Kasper-Virchow, Rainer Kimmig, Stephan Lang, Ina Pretzell, Tienush Rassaf, Alexander Rösch, Jens T. Siveke, Maja Guberina, Ulrich Sure, Marc Wichert, Michael Ingrisch, Kristian Unger, Jürgen Behr, Daniel Teupser, Christian G. Stief, Julia Mayerle, Nadia Harbeck, Amanda Tufman, Jens Ricke, Lars H. Lindner, Siegfried Priglinger, Günter Höglinger, Sven Mahner, Martin Canis, Lucie Heinzerling, Christine Spitzweg, Alpaslan Tasdogan, Matthias Totzeck, Anja Welt, Marcel Wiesweg, C. Benedikt Westphalen, Reinhard Thasler, Fady Albashiti, Grégoire Montavon, Nicola Miglino, Zsolt Balazs, Michael von Bergwelt-Baildon, Volker Heinemann, Claus Belka, Sylvia Hartmann, Andreas Wicki, Felix Nensa, Dirk Schadendorf, Michael Krauthammer, Klaus-Robert Müller, Martin Schuler, Frederick Klauschen, Jens Kleesiek, Julius Keyl medRxiv — 2026-07

2025

Characterizing and Predicting End-of-Life Patient Trajectories Using Routine Clinical Data Jonah Bosserhoff, Julius Keyl, Tim Lenfers, Dagmar Führer-Sakel, Marc Wichert, Frederick Klauschen, Martin Schuler, Sylvia Hartmann, Philipp Keyl, Jens Kleesiek medRxiv — 2025-08