https://www.selleckchem.com/pr....oducts/PCI-24781.htm
Moreover, deep neural network is exploited to approximate the GLD. These strategies constitute a new model deep granular feature-label distribution learning (DGFLDL). By taking 8 types of cortical morphometric features from structural MRI as predictors, the proposed DGFLDL is validated on infant age prediction using 384 brain MRI scans from 35 to 848 days after birth. Our proposed method, approaching the mean absolute error as 36.1 days, significantly outperforms the baseline methods. Besides, the permutation importance analysis of fe
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