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A Framework For Memory Performance Prediction From Brain Volume In Preterm-Born Adolescents

Irzan, H; O'Reilly, H; Ourselin, S; Marlow, N; Melbourne, A; (2019) A Framework For Memory Performance Prediction From Brain Volume In Preterm-Born Adolescents. In: 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019). (pp. pp. 400-403). IEEE: Venice, Italy. Green open access

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Abstract

With advances in medical care, higher numbers of extremely preterm-born babies are now surviving, however the rate of neurodevelopmental and neurological complications has not improved at the same rate and the relative rate of disabilities and health problems is increasing, with associated high costs for health care systems and education. Understanding brain development after early birth is of great importance to be able to make informed decisions. Many studies have associated different areas of the preterm brain with poor cognitive performance, however it is less clear whether these associations persist into adult life. In this study, we investigate how well cortical volumes describe memory performance in 133 19 year-old adolescents, 61% of whom were born extremely preterm. We employ LASSO to identify brain regions that better explain memory performance. The brain regions identified by LASSO explained 27% and 32% of the variance in the visual working memory scores and the visual short term memory respectively. Furthermore, the correlation between the predicted scores and validation scores is statistically significant and it is 58% for the visual working memory task and 56% for the visual short term memory task.

Type: Proceedings paper
Title: A Framework For Memory Performance Prediction From Brain Volume In Preterm-Born Adolescents
Event: 16th IEEE International Symposium on Biomedical Imaging (ISBI)
Location: Venice, ITALY
Dates: 08 April 2019 - 11 April 2019
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ISBI.2019.8759452
Publisher version: https://doi.org/10.1109/ISBI.2019.8759452
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 > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Neonatology
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 Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10115542
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