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19 results on '"Young, Alexandra"'

5. Author Correction: Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data

Author

Eshaghi, Arman, primary, Young, Alexandra L., additional, Wijeratne, Peter A., additional, Prados, Ferran, additional, Arnold, Douglas L., additional, Narayanan, Sridar, additional, Guttmann, Charles R. G., additional, Barkhof, Frederik, additional, Alexander, Daniel C., additional, Thompson, Alan J., additional, Chard, Declan, additional, and Ciccarelli, Olga, additional

Published
2021
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7. Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data

Author

Eshaghi, Arman, primary, Young, Alexandra L., additional, Wijeratne, Peter A., additional, Prados, Ferran, additional, Arnold, Douglas L., additional, Narayanan, Sridar, additional, Guttmann, Charles R. G., additional, Barkhof, Frederik, additional, Alexander, Daniel C., additional, Thompson, Alan J., additional, Chard, Declan, additional, and Ciccarelli, Olga, additional

Published
2021
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9. Prion propagation estimated from brain diffusion MRI is subtype dependent in sporadic Creutzfeldt–Jakob disease

Author

Pascuzzo, Riccardo, primary, Oxtoby, Neil P., additional, Young, Alexandra L., additional, Blevins, Janis, additional, Castelli, Gianmarco, additional, Garbarino, Sara, additional, Cohen, Mark L., additional, Schonberger, Lawrence B., additional, Gambetti, Pierluigi, additional, Appleby, Brian S., additional, Alexander, Daniel C., additional, and Bizzi, Alberto, additional

Published
2020
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19. Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

Author

Young, Alexandra L, Marinescu, Razvan V, Oxtoby, Neil P, Bocchetta, Martina, Yong, Keir, Firth, Nicholas C, Cash, David M, Thomas, David L, Dick, Katrina M, Cardoso, Jorge, Van Swieten, John, Borroni, Barbara, Galimberti, Daniela, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B, Graff, Caroline, Tagliavini, Fabrizio, Frisoni, Giovanni B, Laforce, Robert, Finger, Elizabeth, De Mendonça, Alexandre, Sorbi, Sandro, Warren, Jason D, Crutch, Sebastian, Fox, Nick C, Ourselin, Sebastien, Schott, Jonathan M, Rohrer, Jonathan D, Alexander, Daniel C, Genetic FTD Initiative (GENFI), and Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Subjects
Phenotype, Time Factors, Genotype, Alzheimer Disease, Frontotemporal Dementia, Models, Neurological, Humans, Reproducibility of Results, Neurodegenerative Diseases, 3. Good health
Abstract

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique-Subtype and Stage Inference (SuStaIn)-able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer's disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10-4) or temporal stage (p = 3.96 × 10-5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

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