This model detects and localizes lung opacities suspicious for pneumonia on frontal (PA or AP) chest radiographs when a suggestive clinical context is present. Based on the ensemble of a classification model and five instance object detection models, the ensemble model can detect single or multiple distinct opacities on a single image. Bounding boxes are defining the area boundaries of detected lung opacities.
Model performance metrics
Mean average precision = 0.232 Estimated classification AUROC = 0.894 For comparison, classification models in the literature for similar labels (infiltration, pneumonia, consolidation) report AUROC classification performance between 0.609 to 0.790.