Mihalik, A;
Brudfors, M;
Robu, M;
Ferreira, FS;
Lin, H;
Rau, A;
Wu, T;
... Oxtoby, NP; + view all
(2019)
ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression.
In: Pohl, K and Thompson, W and Adeli, E and Linguraru, M, (eds.)
Adolescent Brain Cognitive Development Neurocognitive Prediction. ABCD-NP 2019. Lecture Notes in Computer Science.
(pp. pp. 133-142).
Springer: Cham.
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Abstract
We applied several regression and deep learning methods to predict fluid intelligence scores from T1-weighted MRI scans as part of the ABCD Neurocognitive Prediction Challenge 2019. We used voxel intensities and probabilistic tissue-type labels derived from these as features to train the models. The best predictive performance (lowest mean-squared error) came from kernel ridge regression ($$\lambda =10$$), which produced a mean-squared error of 69.7204 on the validation set and 92.1298 on the test set. This placed our group in the fifth position on the validation leader board and first place on the final (test) leader board.
| Type: | Proceedings paper |
|---|---|
| Title: | ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression |
| Event: | Adolescent Brain Cognitive Development Neurocognitive Prediction. ABCD-NP 2019. |
| ISBN-13: | 9783030319007 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-31901-4_16 |
| Publisher version: | https://doi.org/10.1007/978-3-030-31901-4_16 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10075020 |
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