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Quibim has developed the Chest X-ray Classifier to help radiology departments be more efficient. This AI-fueled app is able to automatically identify PA/AP acquisitions and estimate the presence probability of 15 different findings in chest radiographs. Once these 15 probabilities are calculated, the classifier combines them to quantify the final abnormal probability of an image.

The app provides heatmaps that are displayed over the analyzed radiographs and that show the level of influence of each region of an image in the final abnormality score. By segmenting both lungs, the app extracts textural features to foster posterior radiomic studies.

Quibim’s app helps radiologists deal with the large volumes of chest radiographs that are generated in health centers every day, by prioritizing potentially pathological cases.


  • Atelectasis
  • Cardiomegaly
  • Consolidation
  • Edema
  • Emphysema
  • Enlarged Cardiomediastinum
  • Fibrosis
  • Fracture
  • Hernia
  • Lung lesion
  • Lung opacity
  • Pleural effusion
  • Pleural thickening
  • Pneumothorax
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