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Found 3 papers, 1 papers with code
Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography
We show, that lung X-ray masks created by following the contours of the heart, mediastinum, and diaphragm significantly underestimate lung regions and exclude substantial portions of the lungs from further assessment, which may result in numerous clinical errors.
Prevention is better than cure: a case study of the abnormalities detection in the chest
Based on this use case, we show how to monitor data and model balance (fairness) throughout the life cycle of a predictive model, from data acquisition to parity analysis of model scores.
Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies
The sudden outbreak and uncontrolled spread of COVID-19 disease is one of the most important global problems today.
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