
Latest multimodal large language models show limitations on image-based radiology exam questions.
Key Details
- 1Researchers tested ChatGPT-4v and ChatGPT-4o on 222 image-based multiple-choice questions from national radiology board exams (2020 and 2024).
- 2These LLMs have been recently trained to process both text and images.
- 3Despite advancements, significant concerns remain regarding their reliability for diagnostic tasks in radiology.
- 4The potential of such models in radiology workflows, such as report generation and diagnostic support, is still under early investigation.
Why It Matters
As large language models gain capability for image analysis, assessing their reliability is crucial for safe deployment in radiology. Failures on board-style questions highlight the need for ongoing scrutiny before clinical trust is warranted.

Source
Radiology Business
Related News

•AuntMinnie
AI Model Uses Ultrasound to Assess Fetal Lung Maturity
Researchers demonstrated an AI model's strong accuracy in measuring fetal lung maturity from ultrasound images.

•AuntMinnie
AI Model Predicts Dosimetry for Lu-177 PSMA Therapy Using PET/CT
A machine learning PET/CT model shows promise for predicting radiation dose prior to Lu-177 PSMA therapy in prostate cancer patients.

•Radiology Business
AI Concerns Influence Medical Students' Interest in Radiology
AI is deterring a significant portion of medical students from choosing radiology as a career, though most remain optimistic about AI's benefits for the field.