Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning

HIGHLIGHTS

• who: Ekin Tiu from the Stanford University have published the research work: Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning, in the Journal: (JOURNAL) of 30/Nov/2021
• what: By comparing the model output for the positive and negative prompts the self-supervised method computes a probability score for the pathology and this can be used to classify its presence in the chest X-ray image. performance = -0.005; 95% confidence interval (CI) -0.043 0.034) between the performance of the model (0.523; 95% CI 0 . . .
  

   

  

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