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From BERT to generative AI - Comparing encoder-only vs. large language models in a cohort of lung cancer patients for named entity recognition in unstructured medical reports

Journal article

Fast facts

  • Further publishers

    Kamyar Arzideh, Héctor Allende-Cid, Giulia Baldini, Thomas Hilser, Master of Science Ahmad Idrissi-Yaghir, Katharina Laue, Nilesh Chakraborty, Niclas Doll, Dario Antweiler, Katrin Klug, Niklas Beck, Sven Giesselbach, Felix Nensa, Martin Schuler, René Hosch

  • Publishment

    • Elsevier (Amsterdam) 2025
  • Purpose of publication

  • Organizational unit

  • Subjects

    • General medicine
    • Applied computer science
  • Research structures

    • Medical Informatics (MI)
  • Research fields

    • Information systems
    • Artificial intelligence and big data
    • Life and well-being - General

Quote

K. Arzideh, H. Schäfer, H. Allende-Cid, G. Baldini, T. Hilser, A. Idrissi-Yaghir, K. Laue, N. Chakraborty, N. Doll, D. Antweiler, K. Klug, N. Beck, S. Giesselbach, C. M. Friedrich, F. Nensa, M. Schuler, and R. Hosch, "From BERT to generative AI - Comparing encoder-only vs. large language models in a cohort of lung cancer patients for named entity recognition in unstructured medical reports," Computers in Biology and Medicine, vol. 195, p. 110665, 2025.

References

DOI 10.1016/j.compbiomed.2025.110665

Notes and references

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