Fig. 5: Performance of DNN in the prediction of BOS.
From: Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT
Deep network prediction of future onset BOS in patients with relative FEV1 in the range of 90–80% (orange) and 100–90% (blue). Left: aggregated ROC curves. Right: ROC-AUC computed on individual splits. The box extends from the first quartile (Q1) to the third quartile (Q3) of the data, with a line at the median. The whiskers extend from the box to the farthest data point lying within 1.5x the interquartile range (IQR) from the box. Flier points are those past the end of the whiskers. The number of data points for each box plot is 5 (n = 5). FEV1 forced expiratory volume in the first second, BOS bronchiolitis obliterans syndrome.
