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, Ulf P. Neumann, Frederick Klauschen, Sylvia Hartmann, Martin Schuler, Philipp Keyl, Jens Kleesiek, Julius Keyl

Open source

DOI
10.1371/journal.pdig.0001546
Published
2026-07-08
Container
PLOS Digital Health
Publisher
Public Library of Science (PLoS)
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1371/journal.pdig.0001546,
  title = {Large language models enable prognostic stratification of cancer patients using real-world clinical notes},
  author = {Niklas Kiermeyer and Tim Lenfers and Amin Dada and Julian Friedrich and Sameh Khattab and Eric Knop and Jan Egger and Markus Pauly and Andreas Jung and Grégoire Montavon and Jens T. Siveke and Marcel Wiesweg and Stefan Kasper and Ulf P. Neumann and Frederick Klauschen and Sylvia Hartmann and Martin Schuler and Philipp Keyl and Jens Kleesiek and Julius Keyl},
  year = {2026},
  journal = {PLOS Digital Health},
  doi = {10.1371/journal.pdig.0001546},
  url = {https://doi.org/10.1371/journal.pdig.0001546}
}

RIS

TY  - JOUR
TI  - Large language models enable prognostic stratification of cancer patients using real-world clinical notes
AU  - Niklas Kiermeyer
AU  - Tim Lenfers
AU  - Amin Dada
AU  - Julian Friedrich
AU  - Sameh Khattab
AU  - Eric Knop
AU  - Jan Egger
AU  - Markus Pauly
AU  - Andreas Jung
AU  - Grégoire Montavon
AU  - Jens T. Siveke
AU  - Marcel Wiesweg
AU  - Stefan Kasper
AU  - Ulf P. Neumann
AU  - Frederick Klauschen
AU  - Sylvia Hartmann
AU  - Martin Schuler
AU  - Philipp Keyl
AU  - Jens Kleesiek
AU  - Julius Keyl
PY  - 2026
JO  - PLOS Digital Health
DO  - 10.1371/journal.pdig.0001546
UR  - https://doi.org/10.1371/journal.pdig.0001546
ER  - 

APA

Kiermeyer, N., Lenfers, T., Dada, A., Friedrich, J., Khattab, S., Knop, E., Egger, J., Pauly, M., Jung, A., Montavon, G., Siveke, J. T., Wiesweg, M., Kasper, S., Neumann, U. P., Klauschen, F., Hartmann, S., Schuler, M., Keyl, P., Kleesiek, J., & Keyl, J. (2026). Large language models enable prognostic stratification of cancer patients using real-world clinical notes. PLOS Digital Health. https://doi.org/10.1371/journal.pdig.0001546

Source records