The AMA’s warning about using AI for diagnosis and treatment decisions gets to the heart of a growing issue in healthcare: access to information is not the same thing as medical expertise.
AI tools can be helpful for simplifying terminology, organizing information, or helping patients prepare questions for their physician. But there is a major difference between gathering information and making clinical decisions.
In radiology, that distinction matters every day.
MRI interpretation is rarely straightforward. A single study often requires correlation with patient history, prior imaging, physical symptoms, surgical considerations, and conversations with referring physicians. Subtle findings can dramatically change a diagnosis, treatment recommendation, or surgical plan. That level of interpretation depends on experience, subspecialty training, and clinical judgment.
AI does not assume responsibility for patient outcomes. Physicians do.
We also support efforts to establish clear guardrails around how AI is presented in healthcare settings. Patients deserve transparency about whether information is coming from a licensed physician or from a software tool generating probabilistic responses.
At Radsource, we believe technology should strengthen radiologists, not sideline them. AI may continue to improve workflow efficiency and assist with prioritization or data organization, but patient care still depends on highly trained physicians who understand the full clinical picture.
The future of healthcare should combine advanced technology with physician expertise, not confuse one for the other.
