Use of Open-Source Large Language Models for Automatic Synthesis of the Entire Imaging Medical Records of Patients: A Feasibility Study.

Journal: Tomography (Ann Arbor, Mich.)
PMID: 40278714

Abstract

BACKGROUND/OBJECTIVES: Reviewing the entire history of imaging exams of a single patient's records is an essential step in clinical practice, but it is time and resource consuming, with potential negative effects on workflow and on the quality of medical decisions. The main objective of this study was to evaluate the applicability of three open-source large language models (LLMs) for the automatic generation of concise summaries of patient's imaging records. Secondary objectives were to assess correlations among the LLMs and to evaluate the length reduction provided by each model.

Authors

  • Fabio Mattiussi
    Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland.
  • Francesco Magoga
    Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland.
  • Simone Schiaffino
    Imaging Institute of Southern Switzerland (IIMSI), Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.
  • Vittorio Ferrari
  • Ermidio Rezzonico
    Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland.
  • Filippo Del Grande
    Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland.
  • Stefania Rizzo
    Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.

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