Adolescent Brain Cognitive Development Neurocognitive Prediction

Chapter 1 A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction

Chapter 2 Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet

Chapter 3 Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction

Chapter 4 Surface-Based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019

Chapter 5 Prediction of Fluid Intelligence from T1-Weighted Magnetic Resonance Images

Chapter 6 Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI

Chapter 7 Predicting Intelligence Based on Cortical WM/GM Contrast, Cortical Thickness and Volumetry

Chapter 8 Predict Fluid Intelligence of Adolescent Using Ensemble Learning

Chapter 9 Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach

Chapter 10 Predicting Fluid Intelligence from Structural MRI Using Random Forest regression

Chapter 11 Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data

Chapter 12 An AutoML Approach for the Prediction of Fluid Intelligence from MRI-Derived Features

Chapter 13 Predicting Fluid Intelligence from MRI Images with Encoder-Decoder Regularization

Chapter 14 ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology

Chapter 15 Ensemble Modeling of Neurocognitive Performance Using MRI-Derived Brain Structure Volumes

Chapter 16 ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression

Chapter 17 Predicting Fluid Intelligence Using Anatomical Measures Within Functionally Defined Brain Networks

Chapter 18 Sex Differences in Predicting Fluid Intelligence of Adolescent Brain from T1-Weighted MRIs

Chapter 19 Ensemble of 3D CNN Regressors with Data Fusion for Fluid Intelligence Prediction

Chapter 20 Adolescent Fluid Intelligence Prediction from Regional Brain Volumes and Cortical Curvatures Using BlockPC-XGBoost

Chapter 21 Cortical and Subcortical Contributions to Predicting Intelligence Using 3D ConvNets