M3Net achieves state-of-the-art accuracies of 86.96% on LIDC-IDRI and 84.24% on USTC-FHLN for pulmonary nodule classification using a hierarchical multi-scale 3D network with cross-scale consistency.
Explainable machine learning model based on clinical factors for predicting the disappearance of indeterminate pulmonarynodules.Computersinbiologyandmedicine169,107871
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M3Net: A Macro-to-Meso-to-Micro Clinical-inspired Hierarchical 3D Network for Pulmonary Nodule Classification
M3Net achieves state-of-the-art accuracies of 86.96% on LIDC-IDRI and 84.24% on USTC-FHLN for pulmonary nodule classification using a hierarchical multi-scale 3D network with cross-scale consistency.