Tim Lenfers

Tim Lenfers

PhD Student, RWD xAI
Institute for AI in Medicine, Germany
Tim graduated with an M.Sc. in Medical Informatics from the University of Lübeck and completed his master’s thesis at the Heart & Lung Research Institute, University of Cambridge, focusing on computational genomics. He joined the Institute for AI in Medicine (IKIM) as a PhD student in 2024. Tim’s research is centred on identifying digital tumour signatures and biomarkers to quantify oncological disease progression by analysing multimodal clinical datasets. His aim is to develop methods that provide prospective added value in diagnostic and therapeutic applications, effectively bridging the gap between data science and clinical practice.

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 Large language models enable prognostic stratification of cancer patients using real-world clinical notes Niklas Kiermeyer, Tim Lenfers, Amin Dada, Julian Friedrich, Sameh Khattab, Eric Knop, Jan Egger, Markus Pauly, Andreas Jung, Grégoire Montavon, Jens T. Siveke, Marcel Wiesweg, Stefan Kasper-Virchow, Ulf Peter Neumann, Frederick Klauschen, Sylvia Hartmann, Martin Schuler, Philipp Keyl, Jens Kleesiek, Julius Keyl PLOS Digital Health Umsetzung der Leitlinienempfehlungen einer organprotektiven Therapie bei Menschen mit Typ-2-Diabetes und Herz-Kreislauf-Erkrankungen, Herzinsuffizienz oder Nierenerkrankungen: Erkenntnisse aus der Praxis einer deutschen Universitätsklinik Karzan Suliman, Young Hee Lee-Barkey, Alexander Brehmer, Bernd Stratmann, Jasmin M. Klose, Tim Lenfers, Jens Kleesiek, Susanne Reger-Tan, Julius Keyl Diabetologie und Stoffwechsel Explainable AI Predicts Hematoxicity from Cancer Treatment Using Multimodal Real-World Data Julius Keyl, Philipp Keyl, Tim Lenfers, René Hosch, Niklas Kiermeyer, Simon Schallenberg, Moon Kim, Sebastian Bauer, Nikolaos Bechrakis, Michael Forsting, Dagmar Führer-Sakel, Sied Kebir, Viktor Grünwald, Boris Hadaschik, Johannes Haubold, Ken Herrmann, Stefan Kasper-Virchow, Rainer Kimmig, Stephan Lang, Tienush Rassaf, Alexander Rösch, Dirk Schadendorf, Jens T. Siveke, Martin Stuschke, Ulrich Sure, Matthias Totzeck, Anja Welt, Marcel Wiesweg, Jan Egger, Sylvia Hartmann, Grégoire Montavon, Felix Nensa, Klaus-Robert Müller, Martin Schuler, Jens Kleesiek, Frederick Klauschen medRxiv Implementation of guideline-recommended organ-protective therapy in people with type 2 diabetes and cardiovascular disease, heart failure, or kidney disease: real-world evidence from a German University Hospital Karzan Suliman, Young Hee Lee-Barkey, Alexander Brehmer, Bernd Stratmann, Jasmin M. Klose, Tim Lenfers, Jens Kleesiek, Susanne Reger-Tan, Julius Keyl Frontiers in Endocrinology