Radiologists boost AI severity quantification of COVID-19


A research team from the University of California, San Diego (UCSD) used chest radiographs annotated by their radiologists to perform additional training of a previously developed convolutional neural network (CNN) for localizing and quantifying severity of COVID-19 pneumonia on chest x-rays. The group found that this radiologist-supervised transfer learning approach significantly boosted the model’s detection accuracy.


What’s more, the algorithm’s quantitative analysis of lung involvement correlated well with a semiquantitative method for scoring the extent and degree of lung opacities…



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