Large language models for dermatological image interpretation - a comparative study.

Journal: Diagnosis (Berlin, Germany)
Published Date: May 23, 2025

Abstract

OBJECTIVES: Interpreting skin findings can be challenging for both laypersons and clinicians. Large language models (LLMs) offer accessible decision support, yet their diagnostic capabilities for dermatological images remain underexplored. This study evaluated the diagnostic performance of LLMs based on image interpretation of common dermatological diseases.

Authors

  • Lasse Cirkel
    Institute of Artificial Intelligence, University Hospital Gießen-Marburg, Philipps University, Marburg, Germany.
  • Fabian Lechner
    Institut für Künstliche Intelligenz, Universitätsklinikum Gießen und Marburg, Marburg, Deutschland.
  • Lukas Alexander Henk
    Institute for Digital Medicine, University Hospital Gießen-Marburg, Philipps University, Marburg, Germany.
  • Martin Krusche
    Department of Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Martin C Hirsch
    Ada Health GmbH, Adalbertstraße 20, 10997, Berlin, Germany.
  • Michael Hertl
    Department of Dermatology and Allergology, University Hospital Gießen-Marburg, Philipps University, Marburg, Germany.
  • Sebastian Kuhn
    Institute for Digital Medicine Philipps-University Marburg and University Hospital of Giessen and Marburg, Marburg, Germany.
  • Johannes Knitza
    Institut für Digitale Medizin, Universitätsklinikum Marburg, Philipps-Universität Marburg, Marburg, Deutschland.

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