Adolescent Brain Cognitive Development Neurocognitive Prediction First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Pohl, Kilian M. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Thompson, Wesley K. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Adeli, Ehsan (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Linguraru, Marius George (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11791
• Θέματα: Optical data processing.; Machine learning.; Mathematical statistics.; Data mining.; Image Processing and Computer Vision.; Machine Learning.; Probability and Statistics in Computer Science.; Data Mining and Knowledge Discovery.

This book constitutes the refereed proceedings of the First Challenge in Adolescent Brain Cognitive Development Neurocognitive Prediction, ABCD-NP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. 29 submissions were carefully reviewed and 24 of them were accepted. Som...

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• Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images
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• 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
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• 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.