Here is a number the radiology AI industry would rather not talk about: 4.89.
That is the pooled odds ratio from a 2026 systematic review on automation bias in radiology - published by researchers at Rowan University School of Osteopathic Medicine and covering five controlled studies across mammography, chest radiography, and MRI. An odds ratio of 4.89 means that when an AI system flagged a finding incorrectly, radiologists were nearly five times more likely to miss the correct diagnosis than they would have been without AI assistance at all.
Meanwhile, the industry is celebrating a different number: 1,524. That is the count of FDA-cleared AI algorithms in medical imaging as of March 30, 2026. Seventy-six percent of those cleared algorithms - 1,163 of them - are in radiology. The FDA is clearing roughly 30 new algorithms per month. Sixty-eight were cleared in Q1 2026 alone. The pace is extraordinary. The outcome data tracking whether this wave of tools is improving diagnosis is not.
This…
