A Comparative Bicentric Study on Ultrasound Education for Students: App- and AI-Supported Learning Versus Traditional Hands-on Instruction (AI-Teach Study).

Journal: Academic radiology
Published Date:

Abstract

BACKGROUND: The integration of artificial intelligence (AI) into medical education presents significant opportunities for enhancing teaching methods and student learning outcomes. Despite its potential benefits, the implementation of AI in curricula remains limited and lacks standardized approaches.

Authors

  • Elena Höhne
    Clinic for Radiology and Nuclear Medicine, University Hospital Frankfurt, Frankfurt, Germany (E.H., J.G., P.R., T.V., I.Y.).
  • Eva Bauer
    Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Bonn, Germany (E.B., A.W., F.R.).
  • Claus Bauer
    Department of Rheumatology and Clinical Immunology, Clinic of Internal Medicine III, University Hospital Bonn, Bonn, Germany (C.B., V.S.S.).
  • Valentin Schäfer
    Department of Rheumatology and Clinical Immunology, Clinic of Internal Medicine III, University Hospital Bonn, Bonn, Germany (C.B., V.S.S.).
  • Jennifer Gotta
    Goethe University Hospital Frankfurt, Frankfurt am Main, Germany. jennifergotta@aol.com.
  • Philipp Reschke
    Goethe University Hospital Frankfurt, Frankfurt am Main, Germany.
  • Thomas Vogl
    Clinic for Radiology and Nuclear Medicine, University Hospital Frankfurt, Frankfurt, Germany (E.H., J.G., P.R., T.V., I.Y.).
  • Ibrahim Yel
    Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.
  • Johannes Weimer
    Rudolf Frey Learning Clinic, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (J.W.).
  • Agnes Wittek
    Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Bonn, Germany (E.B., A.W., F.R.).
  • Florian Recker
    Department of Gynecology and Obstetrics, Bonn University Hospital, Bonn, Germany.