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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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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AuntMinnie.com
The AI model is an encoder-decoder model trained to generate a text report given a chest x-ray and most recent comparison (anterior-posterior or posterior-anterior view only). The vision encoder weights were initialized from Vision Transformer (ViT) base and the text decoder weights were initialized from Robustly Optimized BERT Pretraining Approach (RoBERTa) base before training for 30 epochs on a data set of 900,000 chest x-rays (CXRs). cp indicates chest pain; sob = shortness of breath. Image courtesy of JAMA Open Network.
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