preprintmedRxivFeb 7, 2023GREEN OA

Evaluating ChatGPT as an Adjunct for Radiologic Decision-Making

Harvard University · Massachusetts General Hospital

PubMed
Indexed incrossrefpubmed

Abstract

Background

ChatGPT, a popular new large language model (LLM) built by OpenAI, has shown impressive performance in a number of specialized applications. Despite the rising popularity and performance of AI, studies evaluating the use of LLMs for clinical decision support are lacking. PURPOSE: To evaluate ChatGPT's capacity for clinical decision support in radiology via the identification of appropriate imaging services for two important clinical presentations: breast cancer screening and breast pain.

Materials And Methods

We compared ChatGPT's responses to the American College of Radiology (ACR) Appropriateness Criteria for breast pain and breast cancer screening. Our prompt formats included an open-ended (OE) format, where ChatGPT was asked to provide the single most appropriate imaging procedure, and a select all that apply (SATA) format, where ChatGPT was given a list of imaging modalities to assess. Scoring criteria evaluated whether proposed imaging modalities were in accordance with ACR guidelines.

Citation impact

273
total citations
FWCI
Percentile
References
21
Citations per year

Authors

6

Topics & keywords

Keywords
  • Medicine
  • Modalities
  • Breast imaging
  • Breast cancer
  • Workflow
  • BI-RADS
  • Medical physics
  • Modality (human–computer interaction)
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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Funding