A multimodal spatiotemporal network that fuses two timepoint CT scans and clinical data reaches 0.897 accuracy and 0.939 AUC for lung nodule malignancy on a new NLST-based dataset.
t1 Images Alone: When only t0 images were used, model performance dropped signifi- cantly, with Acc falling from 0.8974 to 0.7079, along with decreases in Prec and Rec
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CSF-Net: Cross-Modal Spatiotemporal Fusion Network for Pulmonary Nodule Malignancy Predicting
A multimodal spatiotemporal network that fuses two timepoint CT scans and clinical data reaches 0.897 accuracy and 0.939 AUC for lung nodule malignancy on a new NLST-based dataset.