A Pipeline for the Automatic Identification of Randomized Controlled Oncology Trials and Assignment of Tumor Entities Using Natural Language Processing.

Journal: Oncology
Published Date: Jun 13, 2025

Abstract

BACKGROUND: Most tools trying to automatically extract information from medical publications are domain agnostic and process publications from any field. However, only retrieving trials from dedicated fields could have advantages for further processing of the data.

Authors

  • Paul Windisch
    European CyberKnife Center, Munich, Germany. paul.windisch@ksw.ch.
  • Fabio Dennstädt
    Department of Radiation Oncology, Kantonsspital St. Gallen, St. Gallen, Switzerland.
  • Carole Koechli
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.
  • Robert Förster
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.
  • Christina Schröder
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.
  • Daniel M Aebersold
    Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Freiburgstrasse, 3010, Bern, Switzerland.
  • Daniel R Zwahlen
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.

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