An AI model can excel in the lab and fail in the clinic. That is why validation is the heart of medical AI. Retrospective studies test the model on historical data; prospective studies test it in real-time clinical use; implementation studies measure the real impact on detection, recalls and patient outcomes.
The strongest evidence is prospective and independent — carried out by researchers with no financial interest in the product, on populations representative of real patients. Landmark studies, such as the large Scandinavian trials, have tested AI-supported screening against standard double reading in real programmes.
The evidence ladder
- Retrospective: model tested on historical images
- Prospective: model tested in real clinical conditions
- Implementation: impact measured in real programmes
- Meta-analysis: results pooled across studies