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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Saliency maps using Grad-CAM++ (E and H) show the model’s point of interest in chest radiographs (C and F) of patients with achalasia. The model’s point of interest is highlighted with red, yellow, and green. In both the upper and lower panels (E and H), the point of interest is located in a region around the upper esophagus that corresponds to an air esophagogram and/or air-fluid level in the esophagus in the barium esophagogram (D and G).
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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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Saliency maps using Grad-CAM++ (E and H) show the model’s point of interest in chest radiographs (C and F) of patients with achalasia. The model’s point of interest is highlighted with red, yellow, and green. In both the upper and lower panels (E and H), the point of interest is located in a region around the upper esophagus that corresponds to an air esophagogram and/or air-fluid level in the esophagus in the barium esophagogram (D and G).
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