Reshaping free-text radiology notes into structured reports with generative question answering transformers.

Journal: Artificial intelligence in medicine
Published Date: Jun 26, 2024

Abstract

BACKGROUND: Radiology reports are typically written in a free-text format, making clinical information difficult to extract and use. Recently, the adoption of structured reporting (SR) has been recommended by various medical societies thanks to the advantages it offers, e.g. standardization, completeness, and information retrieval. We propose a pipeline to extract information from Italian free-text radiology reports that fits with the items of the reference SR registry proposed by a national society of interventional and medical radiology, focusing on CT staging of patients with lymphoma.

Authors

  • Laura Bergomi
    Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy. Electronic address: laura.bergomi01@universitadipavia.it.
  • Tommaso M Buonocore
    Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
  • Paolo Antonazzo
    Diagnostic Imaging Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.
  • Lorenzo Alberghi
    Diagnostic Imaging Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.
  • Riccardo Bellazzi
    Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
  • Lorenzo Preda
    Unit of Imaging and Radiotherapy, Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy.
  • Chandra Bortolotto
    Unit of Imaging and Radiotherapy, Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy.
  • Enea Parimbelli
    Telfer School of Management, University of Ottawa, Ottawa, ON, Canada.

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