Quality assessment of radiographs through AI-driven feedback: A randomized comparative study on radiographer response in lateral knee radiographs.
Lysdahlgaard S; Jensen J; Pedersen MRV; Kusk MW · 2026 · Radiography (London, England : 1995)
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Introduction High-quality radiographic positioning is essential for accurate diagnosis in knee imaging. Although artificial intelligence (AI) can assess image quality with high accuracy, its influence on radiographers' clinical…
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Metadata source: Europe PMC · DOI 10.1016/j.radi.2026.103459