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Fig 1.

Artifacts.

(a) normal lung with a regular pleural line, A-lines (green), and lung sliding; (b) infected lung with pleural line broken (red) and fused B-lines (green), (c) subpleural consolidation. Images were taken from the POCUS database [46].

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Fig 1 Expand

Fig 2.

Flowchart for systematic diagnosis of lung diseases by means of LUS.

(DVT—Deep Venous Thrombosis).

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Fig 2 Expand

Table 1.

CNN configurations considered for COVID-19 identification in LUS imagery.

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Table 1 Expand

Fig 3.

Examples of images obtained from LUS videos after pre-processing.

Healthy (first row), pneumonia (second row), and COVID-19 (third row) LUS image classes.

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Fig 3 Expand

Fig 4.

5 × 5-fold cross-validation results: Confusion matrices.

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Table 2.

Overall performance results of the evaluated models (95% C.I.).

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Table 2 Expand

Fig 5.

5 × 5-fold cross-validation results: ACC, BACC, and AUC-ROC ACC, BACC, and AUC-ROC scores boxplots.

Box extends from the Q1 to Q3 quartile values of the data, with a line at the median and a triangle at the mean.

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Fig 5 Expand

Fig 6.

5 × 5-fold cross-validation results: Mean ROC curves and AUC scores (95% C.I.).

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Fig 7.

Post-hoc pairwise comparison using the Wilcoxon signed-rank test with Holm correction.

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Fig 7 Expand

Table 3.

Overall COVID-19 vs pneumonia performance results (95% C.I.).

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Table 3 Expand

Table 4.

Overall COVID-19 vs non-COVID-19 performance results (95% C.I.).

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Table 4 Expand