Researchers evaluated ChatGPT, Gemini, and Copilot for explaining radiology reports to patients.
Key Details
- 1Study published in 'Insights Into Imaging' compared ChatGPT, Gemini, and Copilot.
- 2100 anonymized radiology reports were input into each LLM using a standard prompt.
- 3Outputs were rated on a 3-point scale for understandability, readability, and medical accuracy.
- 4Researchers also assessed each model's use of uncertainty language and quality of patient guidance.
- 5Aim was to determine which LLM most accurately and clearly conveyed imaging findings.
Why It Matters
As patients increasingly access their own imaging reports, reliable and accurate AI explanations can improve understanding while minimizing anxiety and confusion. Ensuring LLMs perform well in this setting could help bridge communication gaps between radiologists and patients.
Source
Radiology Business
Related News
•AuntMinnie
Study: Computer Vision Models Best LLMs in Chest CT Breast Abnormality Detection
Computer vision models (CVMs) surpass large language models (LLMs) in accurately labeling incidental breast abnormalities on chest CT scans.
•AuntMinnie
Deep Learning Models Rival Radiologists for Pancreatic Cancer Detection on CT
Deep-learning models achieved comparable or superior accuracy to experienced radiologists in detecting pancreatic cancer on CT scans, especially for small tumors.
•Radiology Business
Radiology AI Devices at Elevated Risk for FDA Recalls, Study Finds
Radiology AI devices are more likely to face FDA recalls, largely due to deviations from intended use and incomplete clinical data.