Book chapter
Ensemble Modeling of Neurocognitive Performance Using MRI-Derived Brain Structure Volumes
Adolescent Brain Cognitive Development Neurocognitive Prediction, pp.124-132
Lecture Notes in Computer Science, Springer International Publishing
10/10/2019
DOI: 10.1007/978-3-030-31901-4_15
Abstract
Prediction of cognitive performance from brain structural imaging data is a challenging machine learning topic. Participating in the ABCD Neurocognitive prediction challenge (2019), we implemented several machine learning models to solve this problem. Our results show superior performance from models relying on boosted decision trees and we find benefit from using two different sets of derived brain volumetric features. Lastly, across all models, we report an increase in performance by ensembling several different model types together in a final layer.
Details
- Title: Subtitle
- Ensemble Modeling of Neurocognitive Performance Using MRI-Derived Brain Structure Volumes
- Creators
- Leo Brueggeman - University of Iowa, Iowa City, USATanner Koomar - University of Iowa, Iowa City, USAYongchao Huang - University of Iowa, Iowa City, USABrady Hoskins - University of Iowa, Iowa City, USATien Tong - University of Iowa, Iowa City, USAJames Kent - University of Iowa, Iowa City, USAEthan Bahl - University of Iowa, Iowa City, USACharles E Johnson - University of Iowa, Iowa City, USAAlexander Powers - University of Iowa, Iowa City, USADouglas Langbehn - University of Iowa, Iowa City, USAJatin Vaidya - University of Iowa, Iowa City, USAHans Johnson - University of Iowa, Iowa City, USAJacob J Michaelson - University of Iowa, Iowa City, USA
- Resource Type
- Book chapter
- Publication Details
- Adolescent Brain Cognitive Development Neurocognitive Prediction, pp.124-132
- Publisher
- Springer International Publishing; Cham
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-030-31901-4_15
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Language
- English
- Date published
- 10/10/2019
- Academic Unit
- Communication Sciences and Disorders; University College Courses; Electrical and Computer Engineering; Psychological and Brain Sciences; Roy J. Carver Department of Biomedical Engineering; The Iowa Initiative for Artificial Intelligence; Iowa Neuroscience Institute; Psychiatry; The Iowa Institute for Biomedical Imaging; Iowa Informatics Initiative
- Record Identifier
- 9984070850802771
Metrics
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