
ChatGPT (GPT-4) demonstrated high accuracy in identifying clinically significant breast pain symptoms that require imaging evaluation.
Key Details
- 1Research published in Clinical Imaging tested ChatGPT (GPT-4) on triaging breast pain.
- 2ChatGPT correctly classified the clinical significance in nearly 75% of cases overall.
- 3It accurately identified 89% of cases deemed by radiologists as needing further evaluation.
- 4This could allow non-physician staff to safely triage imaging referrals with nurse oversight.
- 5Automated triage addresses rising workload and prolonged wait times.
Why It Matters

Source
Radiology Business
Related News

Toronto Study: LLMs Must Cite Sources for Radiology Decision Support
University of Toronto researchers found that large language models (LLMs) such as DeepSeek V3 and GPT-4o offer promising support for radiology decision-making in pancreatic cancer when their recommendations cite guideline sources.

AI Model Using Mammograms Enhances Five-Year Breast Cancer Risk Assessment
A new image-only AI model more accurately predicts five-year breast cancer risk than breast density alone, according to multinational research presented at RSNA 2025.

AI Model Uses CT Scans to Reveal Biomarker for Chronic Stress
Researchers developed an AI model to measure chronic stress using adrenal gland volume on routine CT scans.