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. 2020 Jul 22;2(4):e200079. doi: 10.1148/ryai.2020200079

Figure 3:

Siamese neural network-based Pulmonary X-Ray Severity (PXS) score can be used to assess longitudinal change in radiographic disease severity over time in COVID-19 patients. A, Boxplot shows the PXS score correlates with majority vote change in pulmonary disease severity (ρ=0.74, P<0.001), where -1, 0, and 1 indicate decreased, unchanged, and increased severity in longitudinal chest radiograph pairs, assigned by three independent raters (2 thoracic radiologists, 1 in-training radiologist). The boxplot boxes indicate the median and interquartile range (IQR), with whiskers extending to points within 1.5 IQRs of the IQR boundaries. B, Examples of PXS score evaluation of longitudinal change in three patients with COVID-19.

Siamese neural network-based Pulmonary X-Ray Severity (PXS) score can be used to assess longitudinal change in radiographic disease severity over time in COVID-19 patients. A, Boxplot shows the PXS score correlates with majority vote change in pulmonary disease severity (ρ=0.74, P<0.001), where -1, 0, and 1 indicate decreased, unchanged, and increased severity in longitudinal chest radiograph pairs, assigned by three independent raters (2 thoracic radiologists, 1 in-training radiologist). The boxplot boxes indicate the median and interquartile range (IQR), with whiskers extending to points within 1.5 IQRs of the IQR boundaries. B, Examples of PXS score evaluation of longitudinal change in three patients with COVID-19.