{ "item_title" : "Adolescent Brain Cognitive Development Neurocognitive Prediction", "item_author" : [" Kilian M. Pohl", "Wesley K. Thompson", "Ehsan Adeli "], "item_description" : "A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction.- Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet.- Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction.- Surface-based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019.- Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images.- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI.- Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry.- Predict Fluid Intelligence of Adolescent Using Ensemble Learning.- Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach.- Predicting Fluid intelligence from structural MRI using Random Forest regression.- Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data.- An AutoML Approach for the Prediction of Fluid Intelligence From MRI-Derived Features.- Predicting Fluid Intelligence from MRI images with Encoder-decoder Regularization.- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology.- Ensemble Modeling of Neurocognitive Performance Using MRI-derived Brain Structure Volumes.- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression.- Predicting fluid intelligence using anatomical measures within functionally defined brain networks.- Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs.- Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction.- Adolescent fluid intelligence prediction from regional brain volumes and cortical curvatures using BlockPC-XGBoost.- Cortical and Subcortical Contributions to Predicting Intelligence using 3D ConvNets.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/03/031/900/3030319008_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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