| Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences AP Carrieri, N Haiminen, S Maudsley-Barton, LJ Gardiner, B Murphy, ... Scientific reports 11 (1), 4565, 2021 | 73 | 2021 |
| pySuStaIn: a Python implementation of the Subtype and Stage Inference algorithm LM Aksman, PA Wijeratne, NP Oxtoby, A Eshaghi, C Shand, A Altmann, ... SoftwareX 16, 100811, 2021 | 24 | 2021 |
| Evolving controllably difficult datasets for clustering C Shand, R Allmendinger, J Handl, A Webb, J Keane Proceedings of the Genetic and Evolutionary Computation Conference, 463-471, 2019 | 15 | 2019 |
| Targeted Screening for Alzheimer's Disease Clinical Trials Using Data-Driven Disease Progression Models NP Oxtoby, C Shand, DM Cash, DC Alexander, F Barkhof Frontiers in Artificial Intelligence 5, 660581, 2022 | 9 | 2022 |
| HAWKS: Evolving challenging benchmark sets for cluster analysis C Shand, R Allmendinger, J Handl, A Webb, J Keane IEEE Transactions on Evolutionary Computation 26 (6), 1206-1220, 2021 | 6 | 2021 |
| Artificial intelligence for dementia research methods optimization M Bucholc, C James, AA Khleifat, AP Badhwar, N Clarke, A Dehsarvi, ... Alzheimer's & Dementia 19 (12), 5934-5951, 2023 | 5 | 2023 |
| Uncovering spatiotemporal patterns of atrophy in progressive supranuclear palsy using unsupervised machine learning WJ Scotton, C Shand, E Todd, M Bocchetta, DM Cash, L VandeVrede, ... Brain communications 5 (2), fcad048, 2023 | 5 | 2023 |
| Heterogeneity in preclinical Alzheimer’s disease trial cohort identified by image-based data-driven disease progression modelling C Shand, PJ Markiewicz, DM Cash, DC Alexander, MC Donohue, ... medRxiv, 2023 | 2 | 2023 |
| Towards an adaptive encoding for evolutionary data clustering C Shand, R Allmendinger, J Handl, J Keane Proceedings of the Genetic and Evolutionary Computation Conference, 521-528, 2018 | 1 | 2018 |
| Combining multimodal connectivity information improves modelling of pathology spread in Alzheimer’s disease E Thompson, A Schroder, T He, C Shand, S Soskic, NP Oxtoby, F Barkhof, ... Imaging Neuroscience 2, 1-19, 2024 | | 2024 |
| Distinct spatiotemporal atrophy patterns in corticobasal syndrome are associated with different underlying pathologies WJ Scotton, C Shand, E Todd, M Bocchetta, DM Cash, L VandeVrede, ... medRxiv, 2024.03. 14.24304298, 2024 | | 2024 |
| Computational progression subtypes of hypometabolism due to Alzheimer’s disease: towards linking antemortem and postmortem diagnoses NP Oxtoby, C Shand, P Bourgeat Alzheimer's & Dementia 19, e079521, 2023 | | 2023 |
| What time window do AD trajectories depart from normal? Estimating age‐related trajectories to chart preclinical phase of Alzheimer’s disease and select trial‐ready cohorts DM Cash, S Verdi, C Shand, W Coath, SE Keuss, A O'Connor, A Bollack, ... Alzheimer's & Dementia 19, e078143, 2023 | | 2023 |
| Data‐driven neuroanatomical subtype trajectories of primary progressive aphasia B Taylor, M Bocchetta, C Shand, EG Todd, A Chokesuwattanaskul, ... Alzheimer's & Dementia 19, e076663, 2023 | | 2023 |
| Correction to: Uncovering spatiotemporal patterns of atrophy in progressive supranuclear palsy using unsupervised machine learning WJ Scotton, C Shand, E Todd, M Bocchetta, DM Cash, L VandeVrede, ... Brain Communications 5 (6), 2023 | | 2023 |
| Bayesian inference of a new Mallows model for characterising symptom sequences applied in primary progressive aphasia B Taylor, C Shand, CJD Hardy, N Oxtoby arXiv preprint arXiv:2311.13411, 2023 | | 2023 |
| Investigating neurodegenerative heterogeneity in cognitively unimpaired A4 pre‐randomization cohort C Shand, MC Donohue, NP Oxtoby Alzheimer's & Dementia 18, e061456, 2022 | | 2022 |
| Evolutionary Algorithms in Clustering: Challenging Problem Generation and Search Space Adaptation C Shand The University of Manchester, 2020 | | 2020 |
Neil P. OxtobyPrincipal Research Associate and UKRI Future Leaders Fellow, University College LondonVerified email at ucl.ac.uk
