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A kinetic approach to consensus-based segmentation of biomedical images
In this work, we apply a kinetic version of a bounded confidence consensus model to biomedical segmentation problems.
Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade oftwo U-nets: training and assessment on multipledatasets using different annotation criteria
On an independent and publicly available benchmark dataset, the Dice values measured between the masks predicted by LungQuant system and the reference ones were 0. 95$\pm$0. 01 and 0. 66$\pm$0. 13 for the segmentation of lungs and COVID-19 lesions, respectively.
A new approach in model selection for ordinal target variables
This paper introduces a novel approach to assess model performance for predictive models characterized by an ordinal target variable in order to satisfy the lack of suitable tools in this framework.
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