ChatGPT in Radiology: Your Extra Set of Digital Eyes
ChatGPT isn’t replacing radiologist
Imagine having a 24/7 colleague in the reading room — one who never gets fatigued, can describe some shadow son an X-ray in seconds, and is always ready to suggest what it might mean. That’s what ChatGPT-4 promises for radiology: an extra set of digital eyes. (Ref: https://arxiv.org/pdf/2501.06269)
In tests based on the reference with chest X-rays, it could spot patterns like pneumonia or COVID-19 changes and explain its reasoning step-by-step.
During on calls this can speed up triage, help junior radiologists learn, and even support clinics in remote areas with no radiologist on site.
But here’s the fuzz:
- No access to full health records – It can’t combine imaging with lab results, patient history, or other scans, which is often critical for accurate diagnosis.EMR are not ready to be connected to ChatGPT.
- Struggles with fine distinctions – Thorax is the most challeging radiology arena when differentiating bacterial from viral pneumonia, or spotting subtle findings, is still hit-and-miss. or because of superposition. e. g. COPD+pneumonia.
- Regulatory & privacy hurdles – Integrating with hospital systems means navigating strict data security rules and ethical concerns.
- Not ready to stand alone – It’s a helpful partner, but the final call must come from a trained radiologist. And sometimes can bias some opinions with junior radiologists.
Bottom line: ChatGPT isn’t replacing radiologists, but it’s already showing how AI can become a powerful second set of eyes — one that’s fast, accessible, and capable of supporting decision-making. The next leap will be connecting those eyes to the full picture of a patient’s health.
PD: There is a great oportunity to build a middle layer agent for radiologists depending of years the of experience, such as a 'Radiology AI Hub Moderator".