Integrating Large language models into radiology workflow: Impact of generating personalized report templates from summary.

Journal: European journal of radiology
Published Date: May 25, 2025

Abstract

OBJECTIVE: To evaluate feasibility of large language models (LLMs) to convert radiologist-generated report summaries into personalized report templates, and assess its impact on scan reporting time and quality.

Authors

  • Amit Gupta
    Department of Cardiology, SKIMS, Srinagar, India. Electronic address: amitcardio12@gmail.com.
  • Manzoor Hussain
    Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi, India. Electronic address: 88manzoor@gmail.com.
  • Kondaveeti Nikhileshwar
    Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi, India. Electronic address: kondaveetinikhil95@gmail.com.
  • Ashish Rastogi
    Department of Radiology, Dr B.R.A.IRCH, All India Institute of Medical Sciences, New Delhi, India. Electronic address: ashishrastogi.3150@gmail.com.
  • Krithika Rangarajan
    Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi, India.

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