Dermacen analytica: A novel methodology integrating multi-modal large language models with machine learning in dermatology.

Journal: International journal of medical informatics
PMID: 40153891

Abstract

OBJECTIVE: To design, implement, evaluate, and quantify a novel and adaptable Artificial Intelligence-empowered methodology aimed at supporting a dermatologist's workflow in assessing and diagnosing skin conditions, leveraging AI's deep image analytic power and reasoning. Skin presents diverse conditions that no single AI solution can comprehensively address, suggesting that mimicking a medical professional's diagnostic process and creating strategic AI interventions may enhance decision-making.

Authors

  • Dimitrios P Panagoulias
    Department of Informatics, University of Piraeus, Piraeus 185 34, Greece. Electronic address: panagoulias_d@unipi.gr.
  • Evridiki Tsoureli-Nikita
    National and Kapodistrian University of Athens, School of Medicine, Greece. Electronic address: evinikita@gmail.com.
  • Maria Virvou
    Department of Informatics, University of Piraeus, Piraeus 185 34, Greece. Electronic address: mvirvou@unipi.gr.
  • George A Tsihrintzis
    Department of Informatics, University of Piraeus, Piraeus 185 34, Greece. Electronic address: geoatsi@unipi.gr.

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