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. 2021 Jan 16;41(1):239–254. doi: 10.1016/j.bbe.2021.01.002

Table 13.

Clinical input by radiologist for misclassified images.

Images Ground truth Prediction Clinical input
graphic file with name fx1_lrg.gif COVID-19 Normal X-ray image of the pediatric patient has less filed of the lung than mediastinum, so the software learning algorithm picks up as normal (healthy).
graphic file with name fx2_lrg.gif COVID-19 Normal No explanation has to correlate with chest auscultation findings.
graphic file with name fx3_lrg.gif Normal COVID-19 X-ray image has an area of retro cardiac opacity and cardiac silhouettes deviation, so the software learning algorithm may have picked up as COVID-19.
graphic file with name fx4_lrg.gif Bacterial Pneumonia COVID-19 X-ray image has hilar lymph nodes and peripheral opacity, so the software learning algorithm may have picked up as COVID-19.
graphic file with name fx5_lrg.gif COVID-19 Normal No explanation has to correlate with chest auscultation findings