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  • We highlight two key findings: (1) our COVID-19 detection model minimizes manual interaction dependent on radiologists as it automates the identification of structural abnormalities in patient’s CXRs and (2) our deep learning model is likely to detect true positives and true negatives and weed out false positive and false negatives with > 96.3% accuracy.
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