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Found 3 papers, 1 papers with code
MERIT: Multi-view Evidential learning for Reliable and Interpretable liver fibrosis sTaging
MERIT enables uncertainty quantification of the predictions to enhance reliability, and employs a logic-based combination rule to improve interpretability.
A Reliable and Interpretable Framework of Multi-view Learning for Liver Fibrosis Staging
Therefore, we propose a reliable multi-view learning method with interpretable combination rules, which can model global representations to improve the accuracy of predictions.
Lung Infection Quantification of COVID-19 in CT Images with Deep Learning
The performance of the system was evaluated by comparing the automatically segmented infection regions with the manually-delineated ones on 300 chest CT scans of 300 COVID-19 patients.
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