PMC:7782580 / 17239-20384 JSONTXT 2 Projects

Annnotations TAB TSV DIC JSON TextAE

Id Subject Object Predicate Lexical cue
T124 0-12 Sentence denotes Experiment-A
T125 13-186 Sentence denotes In this experiment, we used the X-data of the XPVS where the normal cases were from the RSNA data set and the COVID-19 cases were from the COVID CXR data set (CCD) data set.
T126 187-324 Sentence denotes The results of the five evaluation indicators for the comparison of the COVID-19 cases and normal cases of the XPVS are shown in Table 2.
T127 325-435 Sentence denotes An excellent performance was obtained, with the best score of specificity of 99.33% and a precision of 98.33%.
T128 436-625 Sentence denotes The F1 score was 96.72%, which was higher than that of the Respire. (96.12%), the Emerg. (93.94%), the Intern (84.67%), and the Rad-3rd (85.93%) and lower than that of the Rad-5th (98.41%).
T129 626-819 Sentence denotes The kappa index was 95.40%, which was higher than that of the Respire. (94.43%), the Emerg. (91.21%), the Intern (77.45%), and the Rad-3rd (79.42%), and lower than that of the Rad-5th (97.74%).
T130 820-1010 Sentence denotes The sensitivity index was 95.16%, which was higher than that of the Intern (93.55%) and the Rad-3rd (93.55%) and lower than that of the Respire. (100%), the Emerg. (100%) and Rad-5th (100%).
T131 1011-1176 Sentence denotes The receiver operating characteristic (ROC) scores for the CNNCF and the experts are plotted in Fig. 4a; the area under the ROC curve (AUROC) of the CNNCF is 0.9961.
T132 1177-1332 Sentence denotes The precision-recall scores for the CNNCF and the experts are plotted in Fig. 4d; the area under the precision-recall curve (AUPRC) of the CNNCF is 0.9910.
T133 1333-1653 Sentence denotes Table 2 Performance indices of the classification framework (CNNCF) of experiment A and the average performance of the 7th-year respiratory resident (Respira.), the 3rd-year emergency resident (Emerg.), the 1st-year respiratory intern (Intern), the 5th-year radiologist (Rad-5th), and the 3rd-year radiologist (Rad-3rd).
T134 1654-1741 Sentence denotes F1 (95% CI) Kappa (95% CI) Specificity (95% CI) Sensitivity (95% CI) Precision (95% CI)
T135 1742-1750 Sentence denotes CNNCF 0.
T136 1751-1847 Sentence denotes 9672 (0.9307, 0.9890) 0.9540 (0.9030, 0.9924) 0.9933 (0.9792, 1.0000) 0.9516 (0.8889, 1.0000) 0.
T137 1848-1869 Sentence denotes 9833 (0.9444, 1.0000)
T138 1870-1878 Sentence denotes Respire.
T139 1879-1998 Sentence denotes 0.9612 (0.9231, 0.9920) 0.9443 (0.8912, 0.9887) 0.9667 (0.9363, 0.9933) 1.0000 (1.0000, 1.0000) 0.9254 (0.8095, 0.9571)
T140 1999-2005 Sentence denotes Emerg.
T141 2006-2008 Sentence denotes 0.
T142 2009-2126 Sentence denotes 9394 (0.8947, 0.9781) 0.9121 (0.8492, 0.9677) 0.9467 (0.9091, 0.9797) 1.0000 (1.0000, 1.0000) 0.8857 (0.8095, 0.9571)
T143 2127-2134 Sentence denotes Intern.
T144 2135-2253 Sentence denotes 0.8467 (0.7692, 0.9041) 0.7745 (0.6730, 0.8592) 0.8867 (0.8333, 0.9343) 0.9355 (0.8596, 0.984) 0.7733 (0.6708, 0.8649)
T145 2254-2381 Sentence denotes Rad-5th 0.9841 (0.9593, 1.0000) 0.9774 (0.9433, 1.0000) 0.9867 (0.9662, 1.0000) 1.0000 (1.0000, 1.0000) 0.9688 (0.9219, 1.0000)
T146 2382-2509 Sentence denotes Rad-3rd 0.8593 (0.7931, 0.9180) 0.7942 (0.7062, 0.8779) 0.9000 (0.8541, 0.9481) 0.9355 (0.8666, 0.9841) 0.7945 (0.6974, 0.8873)
T147 2510-2573 Sentence denotes Fig. 4 ROC and PRC curves for the CNNCF of the experiments A-C.
T148 2574-2663 Sentence denotes NC indicates that the positive case is a COVID-19 case, and the negative case is *Normal.
T149 2664-2748 Sentence denotes CI indicates that the positive case is COVID-19, and the negative case is influenza.
T150 2749-2835 Sentence denotes The points are the results of experts, corresponding to the results in Tables 2 and 3.
T151 2836-3145 Sentence denotes The background gray dashed curves in the PRC curve correspond to the iso-F1 curves. a ROC curve for the NC using X-data. b ROC curve for the NC using CT-data. c ROC curve for the CI using CT-data. d PRC curve for the NC using X-data. e PRC curve for the NC using CT-data. f PRC curve for the CI using CT-data.