Large language models for structured reporting in radiology: past, present, and future - Summary - MDSpire

Large language models for structured reporting in radiology: past, present, and future

  • By

  • Felix Busch

  • Lena Hoffmann

  • Daniel Pinto dos Santos

  • Marcus R. Makowski

  • Luca Saba

  • Philipp Prucker

  • Martin Hadamitzky

  • Nassir Navab

  • Jakob Nikolas Kather

  • Daniel Truhn

  • Renato Cuocolo

  • Lisa C. Adams

  • Keno K. Bressem

  • October 23, 2024

  • 0 min

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Objective:

Emphasize the significance of LLMs in addressing specific challenges in structured reporting.

Key Findings:
  • Incorporate specific examples or data supporting claims about compliance and error reduction.
Interpretation:

Expand on how LLMs enhance efficiency and accuracy in structured reporting.

Limitations:
  • Provide context on the impact of limitations on clinical practice.
Conclusion:

Address potential risks or challenges associated with LLM implementation.

Original Source(s)

Large language models for structured reporting in radiology: past, present, and future

  • by Felix Busch, Lena Hoffmann, Daniel Pinto dos Santos, Marcus R. Makowski, Luca Saba, Philipp Prucker, Martin Hadamitzky, Nassir Navab, Jakob Nikolas Kather, Daniel Truhn, Renato Cuocolo, Lisa C. Adams, Keno K. Bressem

  • October 23, 2024

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