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DETECTION OF LONGITUDINAL BRAIN ATROPHY PATTERNS CONSISTENT WITH PROGRESSION TOWARDS ALZHEIMER’S DISEASE

Published online by Cambridge University Press:  12 November 2018

MARCELA I. CESPEDES*
Affiliation:
CSIRO Health and Biosecurity, 901/16 Royal Brisbane and Women’s Hospital, Herston, Queensland 4029, Australia email marcela.cespedes@csiro.au
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Abstract

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Type
Abstracts of Australasian PhD Theses
Copyright
© 2018 Australian Mathematical Publishing Association Inc. 

Footnotes

Thesis submitted to Queensland University of Technology in November 2017; degree approved on 31 May 2018; principal supervisor James McGree, associate supervisors Kerrie Mengersen, Christopher Drovandi, James Doecke and Jurgen Fripp.

References

Cespedes, M. I., Fripp, J., McGree, J. M., Drovandi, C. C., Mengersen, K. and Doecke, J. D., ‘Comparisons of neurodegeneration over time between healthy ageing and Alzheimer’s disease cohorts via Bayesian inference’, BMJ Open 7(2) (2017), e012174.Google Scholar
Cespedes, M. I., McGree, J., Drovandi, C. C., Mengersen, K., Doecke, J. D., Fripp, J. and Alzheimer’s Disease Neuroimaging Initiative, ‘An efficient algorithm for estimating brain covariance networks’, PLoS ONE 13(7) (2018), e0198583.Google Scholar
Cespedes, M. I., McGree, J., Drovandi, C. C., Mengersen, K., Doecke, J. D. and Fripp, J., ‘A Bayesian hierarchical approach to jointly model structural biomarkers and covariance networks’, Preprint, 2018. Available at https://eprints.qut.edu.au/112807.Google Scholar
Cespedes, M. I., McGree, J., Drovandi, C. C., Mengersen, K., Doecke, J. D. and Fripp, J., ‘Age dependent network dynamics via Bayesian hierarchical models reveal spatio-temporal patterns of neurodegeneration’, Preprint, 2018. Available at https://eprints.qut.edu.au/122183.Google Scholar