Louis Plesner talks AI x-ray exam reads vs. radiologists'

Will Morton
Sep 28, 2023

In an interview with AuntMinnie.com, Louis Plesner, MD, of Herlev and Gentofte Hospital in Copenhagen, Denmark, discussed a study he led that was published September 26 in Radiology that found radiologists outperformed four commercially available algorithms for identifying diseases on chest x-rays.


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Artificial intelligence (AI) assistance facilitates correct fracture identification in cases initially missed by human readers. A representative case is shown using anteroposterior radiographs in a 29-year-old male patient with wrist trauma (suspected nondisplaced transverse scaphoid fracture). The reader’s initial unaided assessment (top) resulted in a missed fracture, whereas with AI assistance (bottom), the fracture was correctly identified. The green box represents the fracture location as predicted by the AI tool, the blue box represents the reference standard annotation, and the red dots represent individual reader annotations.
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TechCare Trauma. Image courtesy of Milvue.
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Example of triage of no change in a pair of chest radiographs in the emergency department. (A) Baseline posteroanterior chest radiograph in a 63-year-old female patient shows a small amount of left (L) pleural effusion and partial atelectasis of the right middle lobe. (B) Follow-up posteroanterior chest radiograph obtained in the same patient 1 day later shows no significant change. (C) Gradient-weighted class activation map shows the algorithm determined no change in the image pair, without relevant highlighting, as the highlighted area is located over the gastroesophageal junction. Image courtesy of Radiology.
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