Artificial Intelligence Language Models to Translate Professional Radiology Mammography Reports Into Plain Language - Impact on Interpretability and Perception by Patients.

Journal: Academic radiology
Published Date: Jun 19, 2025

Abstract

RATIONALE AND OBJECTIVES: This study aimed to evaluate the interpretability and patient perception of AI-translated mammography and sonography reports, focusing on comprehensibility, follow-up recommendations, and conveyed empathy using a survey.

Authors

  • Dusan Pisarcik
    Department of Radiology, Kantonsspital Baden, affiliated Hospital for Research and Teaching of the Faculty of Medicine of the University of Zurich, Baden, Switzerland (D.P., M.K., J.H., M.F., R.A.K.H., A.E.).
  • Marc Kissling
    Department of Radiology, Kantonsspital Baden, affiliated Hospital for Research and Teaching of the Faculty of Medicine of the University of Zurich, Baden, Switzerland (D.P., M.K., J.H., M.F., R.A.K.H., A.E.).
  • Jakob Heimer
    Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057, Zurich, Switzerland.
  • Monika Farkas
    Department of Radiology, Kantonsspital Baden, affiliated Hospital for Research and Teaching of the Faculty of Medicine of the University of Zurich, Baden, Switzerland (D.P., M.K., J.H., M.F., R.A.K.H., A.E.).
  • Cornelia Leo
    Department of Gynecology, Interdisciplinary Breast Center, Kantonsspital Baden, affiliated Hospital for Research and Teaching of the Faculty of Medicine of the University of Zurich, Baden, Switzerland (C.L.).
  • Rahel A Kubik-Huch
    Department of Radiology, Kantonsspital Baden, 1 Im Ergel, Baden, Switzerland.
  • André Euler
    Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland.

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