Predicting fluid intelligence in adolescence from structural MRI with deep learning methods

Susmita Saha, Alex Pagnozzi, Dana Bradford and Jurgen Fripp

Intelligence, 2021, vol. 88, issue C

Abstract: The objective of this study was to investigate the potential of unsegmented structural T1w MR images of adolescent brain for predicting uncorrected/actual fluid intelligence scores without any predefined feature extraction. We also examined whether prediction of uncorrected scores is simply a harder problem from both biological and technical point of view, than prediction of residualised scores.

Keywords: Fluid intelligence; Brain MRI; Deep learning; Adolescence; ABCD Neurocognitive Prediction Challenge 2019; IQ prediction (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intell:v:88:y:2021:i:c:s0160289621000520

DOI: 10.1016/j.intell.2021.101568

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