Figure 3
From: Explainable AI improves task performance in human–AI collaboration
Results of medical experiment. The boxplots compare the task performance between the two treatments: black-box AI and explainable AI. The task performance is measured by the balanced accuracy (A) and the disease detection rate (B) based on the quality assessment of radiologists and the ground-truth labels of the chest X-ray images. A balanced accuracy of 50% provides a naïve baseline corresponding to a random guess (black dotted line). The standalone AI algorithm attains a balanced accuracy of 82.2% and a disease detection rate of 71.4% (orange dashed lines). Statistical significance is based on a one-sided Welch’s t-test (***\(P<0.001\), **\(P<0.01\), *\(P<0.05\)). In the boxplots, the center line denotes the median; box limits are upper and lower quartiles; whiskers are defined as the 1.5x interquartile range.
