2022

Ravi, D., Blumberg, S.B., Ingala, S., Barkhof, F., Alexander, D.C., Oxtoby, N.P. (2022). Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia. MEDICAL IMAGE ANALYSIS, 75 doi:10.1016/j.media.2021.102257

2021

Vogel, J.W., Young, A.L., Oxtoby, N.P., Smith, R., Ossenkoppele, R., Strandberg, O.T., ...Iturria-Medina, Y. (2021). Four distinct trajectories of tau deposition identified in Alzheimer's disease.. Nat Med, doi:10.1038/s41591-021-01309-6
Archetti, D., Young, A.L., Oxtoby, N.P., Ferreira, D., Mårtensson, G., Westman, E., ...Redolfi, A. (2021). Inter-cohort validation of sustain model for alzheimer’s disease. Frontiers in Big Data, 4 doi:10.3389/fdata.2021.661110
Bellio, M., Furniss, D., Oxtoby, N.P., Garbarino, S., Firth, N.C., Ribbens, A., ...Blandford, A. (2021). Opportunities and barriers for adoption of a decision-support tool for Alzheimer’s Disease. ACM Transactions on Computing for Healthcare, doi:10.1145/3462764
Young, A.L., Vogel, J.W., Aksman, L.M., Wijeratne, P.A., Eshaghi, A., Oxtoby, N.P., ...Alexander, D.C. (2021). Ordinal SuStaIn: Subtype and Stage Inference for Clinical Scores, Visual Ratings, and Other Ordinal Data. Frontiers in Artificial Intelligence, 4 doi:10.3389/frai.2021.613261
Aksman, L., Wijeratne, P., Oxtoby, N., Eshaghi, A., Shand, C., Altmann, A., ...Young, A. (2021). pySuStaIn: a Python implementation of the Subtype and Stage Inference algorithm. .
Aksman, L.M., Wijeratne, P.A., Oxtoby, N.P., Eshaghi, A., Shand, C., Altmann, A., ...Young, A.L. (2021). pySuStaIn: A Python implementation of the Subtype and Stage Inference algorithm. SOFTWAREX, 16 doi:10.1016/j.softx.2021.100811
Oxtoby, N., Leyland, L., Aksman, L., Thomas, G., Bunting, E., Wijeratne, P., ...Bremner, F. (2021). Sequence of clinical and neurodegeneration events in Parkinson’s disease progression. Brain: a journal of neurology, doi:10.1093/brain/awaa461
Dekker, I., Schoonheim, M.M., Venkatraghavan, V., Eijlers, A.J.C., Brouwer, I., Bron, E.E., ...Geurts, J.J.G. (2021). The sequence of structural, functional and cognitive changes in multiple sclerosis. NeuroImage: Clinical, 29 doi:10.1016/j.nicl.2020.102550

2020

Vogel, J.W., Young, A.L., Oxtoby, N.P., Smith, R., Ossenkoppele, R., Aksman, L.M., ...Rabinovici, G.D. (2020). Accounting for systematic spatiotemporal variation improves connectome-based models of tau spreading in human Alzheimer’s disease.
Bellio, M., Oxtoby, N.P., Walker, Z., Henley, S., Ribbens, A., Blandford, A., ...Yong, K.X.X. (2020). Analyzing large Alzheimer’s disease cognitive datasets: Considerations and challenges. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 12 e12135. doi:10.1002/dad2.12135
Vogel, J.W., Young, A.L., Oxtoby, N.P., Smith, R., Ossenkoppele, R., Strandberg, O.T., ...Iturria-Medina, Y. (2020). Characterizing the spatiotemporal variability of Alzheimer’s disease pathology. Cold Spring Harbor Laboratory Press.
Archetti, D., Lorenzi, M., Oxtoby, N.P., Alexander, D.C., Frisoni, G.B., Redolfi, A. (2020). Inter-cohort staging efficacy of Gaussian Process Progression Model for Alzheimer’s disease.
Xu, M., Oxtoby, N., Alexander, D.C., Jacob, J. (2020). Learning To Pay Attention To Mistakes..
Oxtoby, N.P. (2020). Piloting a novel screening tool for reducing heterogeneity in clinical trials in Alzheimer’s disease.
Marinescu, R.V., Bron, E.E., Oxtoby, N.P., Young, A.L., Toga, A.W., Weiner, M.W., ...Klein, S. (2020). Predicting Alzheimer’s disease progression: Results from the TADPOLE Challenge.
Firth, N.C., Primativo, S., Brotherhood, E., Young, A.L., Yong, K.X.X., Crutch, S.J., ...Oxtoby, N.P. (2020). Sequences of cognitive decline in typical Alzheimer's disease and posterior cortical atrophy estimated using a novel event-based model of disease progression.. Alzheimers Dement, doi:10.1002/alz.12083
Vogel, J.W., Young, A.L., Oxtoby, N.P., Smith, R., Ossenkoppele, R., Aksman, L.M., ...Medina, Y.I. (2020). Spatiotemporal imaging phenotypes of tau pathology in Alzheimer’s disease.
Aksman, L.M., Oxtoby, N.P., Scelsi, M.A., Wijeratne, P.A., Young, A.L., Alves, I.L., ...Altmann, A. (2020). Tau-first subtype of Alzheimer’s disease progression consistently identified through PET and CSF.
Aksman, L., Oxtoby, N., Scelsi, M., Wijeratne, P., Young, A., Lopes Alves, I., ...Altmann, A. (2020). Tau-first subtype of Alzheimer's disease consistently identified across in vivo and post mortem studies. .
Bellio, M., Oxtoby, N.P., Ribbens, A., Alexander, D.C., Blandford, A. (2020). Testing the conceptual design of icompass: a new clinical decision-support tool to guide clinicians through Alzheimer’s Disease markers’ evolution..

2019

Mihalik, A., Brudfors, M., Robu, M., Ferreira, F.S., Lin, H., Rau, A., ...Tariq, M. (2019). ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression.
Oxtoby, N.P., Ferreira, F.S., Mihalik, A., Wu, T., Brudfors, M., Lin, H., ...Zor, C. (2019). ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology.
Ravi, D., Alexander, D.C., Oxtoby, N.P. (2019). Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression. In Shen, D., Liu, T., Peters, T.M., Staib, L.H., Essert, C., Zhou, S., ...Khan, A. (Eds.), (pp. 164-172). SPRINGER INTERNATIONAL PUBLISHING AG.
Ravì, D., Alexander, D.C., Oxtoby, N.P. (2019). Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression..
Garbarino, S., Lorenzi, M., Oxtoby, N.P., Vinke, E.J., Marinescu, R.V., Eshaghi, A., ...Barkhof, F. (2019). Differences in topological progression profile among neurodegenerative diseases from imaging data.. Elife, 8 doi:10.7554/eLife.49298
Marinescu, R.V., Lorenzi, M., Blumberg, S.B., Young, A.L., Planell-Morell, P., Oxtoby, N.P., ...Golland, P. (2019). Disease Knowledge Transfer Across Neurodegenerative Diseases.
Marinescu, R.V., Eshaghi, A., Lorenzi, M., Young, A.L., Oxtoby, N.P., Garbarino, S., ...Alzheimer's Disease Neuroimaging, I.n.i.t.i.a.t.i.v.e. (2019). DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders.. Neuroimage, doi:10.1016/j.neuroimage.2019.02.053
Firth, N.C., Primativo, S., Marinescu, R.-.V., Shakespeare, T.J., Suarez-Gonzalez, A., Lehmann, M., ...Paterson, R.W. (2019). Longitudinal neuroanatomical and cognitive progression of posterior cortical atrophy.. Brain, doi:10.1093/brain/awz136
Archetti, D., Ingala, S., Venkatraghavan, V., Wottschel, V., Young, A.L., Bellio, M., ...Alexander, D.C. (2019). Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease.. Neuroimage Clin, 24 101954. doi:10.1016/j.nicl.2019.101954
O’Connor, A., Oxtoby, N.P., Weston, P.S.J., Pavisic, I.M., Ryan, N.S., Lu, K., ...Fox, N.C. (2019). O3-03-01: THE SEQUENCE AND TIMING OF PRECLINICAL COGNITIVE DECLINE IN AUTOSOMAL DOMINANT ALZHEIMER’S DISEASE.
Bellio, M., Furniss, D., Firth, N.C., Garbarino, S., Oxtoby, N.P., Ribbens, A., ...Blandford, A. (2019). P3-510: DELIVERING DISEASE PROGRESSION MODELS TO CLINICAL PRACTICE: A USER STUDY ON OPPORTUNITIES AND BARRIERS FOR TRANSLATION AND ADOPTION.
Marinescu, R.V., Oxtoby, N.P., Young, A.L., Bron, E.E., Toga, A.W., Weiner, M.W., ...Klein, S. (2019). TADPOLE challenge: Accurate alzheimer’s disease prediction through crowdsourced forecasting of future data.
Dekker, I., Schoonheim, M.M., Venkatraghavan, V., Eijlers, A.J.C., Brouwer, I., Wattjes, M.P., ...Oxtoby, N.P. (2019). Temporal ordering of multimodal biomarker abnormality in multiple sclerosis.

2018

Wijeratne, P.A., Young, A.L., Oxtoby, N.P., Marinescu, R.V., Firth, N.C., Johnson, E.B., ...Tabrizi, S.J. (2018). An image-based model of brain volume biomarker changes in Huntington's disease. Annals of Clinical and Translational Neurology, doi:10.1002/acn3.558
Oxtoby, N.P., Young, A.L., Cash, D.M., Benzinger, T.L.S., Fagan, A.M., Morris, J.C., ...Alexander, D.C. (2018). Data-driven models of dominantly-inherited Alzheimer's disease progression.. BRAIN, 141 1529-1544. doi:10.1093/brain/awy050
Firth, N., Oxtoby, N., Primativo, S., Brotherhood, E., Young, A., Yong, K.X.X., ...Alexander, D. (2018). Non-Parametric Mixture Modelling and its Application to Disease Progression Modelling. .
Schwarz, A.J., Young, A.L., Risacher, S.L., Charil, A., Shcherbinin, S., Oxtoby, N.P., ...Alexander, D.C. (2018). P1-372: SUBTYPES OF NEURODEGENERATION IN ALZHEIMER DISEASE: A HEAD-TO-HEAD COMPARISON OF FOUR BRAIN ATROPHY SUBTYPE ALGORITHMS IN ADNI.
Garbarino, S., Lorenzi, M., Vinke, E., Marinescu, R.V., Oxtoby, N.P., Eshaghi, A., ...Barkhof, F. (2018). P3-436: MECHANISTIC PROFILES OF NEURODEGENERATION: A STUDY IN ALZHEIMER’S DISEASE, HEALTHY AGEING AND PRIMARY PROGRESSIVE MULTIPLE SCLEROSIS.
Marinescu, R.V., Oxtoby, N.P., Young, A.L., Bron, E.E., Toga, A.W., Weiner, M.W., ...Alexander, D.C. (2018). TADPOLE Challenge: Prediction of Longitudinal Evolution in Alzheimer's Disease. arXiv,

2017

Young, A.L., Marinescu, R.V., Oxtoby, N.P., Bocchetta, M., Cash, D.M., Thomas, D.L., ...van Swieten, J.C. (2017). [IC-P-079]: MULTIPLE DISTINCT ATROPHY PATTERNS FOUND IN GENETIC FRONTOTEMPORAL DEMENTIA USING SUBTYPE AND STAGE INFERENCE (SUSTAIN).
Marinescu, R.V., Primativo, S., Young, A.L., Oxtoby, N.P., Firth, N.C., Eshaghi, A., ...Fox, N.C. (2017). [IC-P-141]: ANALYSIS OF THE HETEROGENEITY OF POSTERIOR CORTICAL ATROPHY: DATA-DRIVEN MODEL PREDICTS DISTINCT ATROPHY PATTERNS FOR THREE DIFFERENT COGNITIVE SUBGROUPS.
Young, A.L., Marinescu, R.V., Yong, K., Firth, N.C., Oxtoby, N.P., Cash, D.M., ...Schott, J.M. (2017). [IC-P-154]: CHARACTERISING THE PROGRESSION OF ALZHEIMER’s DISEASE SUBTYPES USING SUBTYPE AND STAGE INFERENCE (SUSTAIN).
Young, A.L., Marinescu, R.V., Oxtoby, N.P., Bocchetta, M., Cash, D.M., Thomas, D.L., ...van Swieten, J.C. (2017). [P1–443]: MULTIPLE DISTINCT ATROPHY PATTERNS FOUND IN GENETIC FRONTOTEMPORAL DEMENTIA USING SUBTYPE AND STAGE INFERENCE (SUSTAIN).
Young, A.L., Marinescu, R.V., Yong, K., Firth, N.C., Oxtoby, N.P., Cash, D.M., ...Schott, J.M. (2017). [P2–414]: CHARACTERISING THE PROGRESSION OF ALZHEIMER’s DISEASE SUBTYPES USING SUBTYPE AND STAGE INFERENCE (SUSTAIN).
Oxtoby, N.P., Young, A.L., Marinescu, R.V., Alexander, D.C. (2017). [P4–164]: DATA-DRIVEN MODELS OF DISEASE PROGRESSION AND APPLICATIONS TO ALZHEIMER’s DISEASE: EVENT-BASED MODEL AND DIFFERENTIAL EQUATION MODELS OF BIOMARKER CHANGES IN ADNI.
Marinescu, R.V., Eshaghi, A., Lorenzi, M., Young, A.L., Oxtoby, N.P., Garbarino, S., ...Alexander, D.C. (2017). A vertex clustering model for disease progression: Application to cortical thickness images.
Oxtoby, N.P., Garbarino, S., Firth, N.C., Warren, J.D., Schott, J.M., Alexander, D.C. (2017). Data-Driven Sequence of Changes to Anatomical Brain Connectivity in Sporadic Alzheimer's Disease. FRONTIERS IN NEUROLOGY, 8 doi:10.3389/fneur.2017.00580
Oxtoby, N.P., Alexander, D.C. (2017). Imaging plus X: multimodal models of neurodegenerative disease.. Current opinion in neurology, doi:10.1097/wco.0000000000000460

2016

Marinescu, R.V., Young, A.L., Oxtoby, N.P., Firth, N.C., Lorenzi, M., Eshaghi, A., ...Yong, K. (2016). P1-009: A Data-Driven Comparison of the Progression of Brain Atrophy in Posterior Cortical Atrophy and Alzheimer’s Disease.
Bron, E.E., Young, A.L., Oxtoby, N.P., Smits, M., van Swieten, J.C., Wink, A.M., ...Niessen, W.J. (2016). P1-327: Cross-Sectional Modeling of Regional Perfusion and Gray Matter Volume in Alzheimer’s Disease.
Oxtoby, N.P., Young, A.L., Lorenzi, M., Cash, D.M., Weston, P.S.J., Ourselin, S., ...Group, D.I.A.N.S. (2016). P2-144: Model-Based Comparison of Autosomal-Dominant and Late-Onset Alzheimer’s Disease Progression in the Dian and ADNI Studies.
Firth, N.C., Brotherhood, E., Primativo, S., Young, A.L., Marinescu, R.V., Oxtoby, N.P., ...Alexander, D.C. (2016). P3-314: Data-Driven Disease Progression Modelling Using Neuropsychological Tests: Posterior Cortical Atrophy Vs Alzheimer’s Disease.

2015

Young, A.L., Oxtoby, N.P., Ourselin, S., Schott, J.M., Alexander, D.C. (2015). A simulation system for biomarker evolution in neurodegenerative disease. MEDICAL IMAGE ANALYSIS, 26 (1), 47-56. doi:10.1016/j.media.2015.07.004
Young, A.L., Oxtoby, N.P., Huang, J., Marinescu, R.V., Daga, P., Cash, D.M., ...Alexander, D.C. (2015). Multiple orderings of events in disease progression.

2014

Young, A.L., Oxtoby, N.P., Daga, P., Cash, D.M., Fox, N.C., Ourselin, S., ...Alexander, D.C. (2014). A data-driven model of biomarker changes in sporadic Alzheimer's disease. BRAIN, 137 2564-2577. doi:10.1093/brain/awu176
Oxtoby, N.P., Young, A.L., Fox, N.C., Daga, P., Cash, D.M., Ourselin, S., ......o.t.h.e.r.s. (2014). Learning imaging biomarker trajectories from noisy Alzheimer’s disease data using a Bayesian multilevel model.

2013

Rowe, M.C., Zhang, H., Oxtoby, N., Alexander, D.C. (2013). Beyond Crossing Fibers: Tractography Exploiting Sub-voxel Fibre Dispersion and Neighbourhood Structure. In Information Processing in Medical Imaging - IPMI 2013. (pp. 402-413). Springer.
Oxtoby, N.P., Griffith, E.J., Durniak, C., Ralph, J.F., Samsonov, D. (2013). Ideal Gas Behavior of a Strongly Coupled Complex (Dusty) Plasma. PHYSICAL REVIEW LETTERS, 111 (1), doi:10.1103/PhysRevLett.111.015002

2012

Oxtoby, N.P., Griffith, E.J., Samsonov, D., Ralph, J.F., Durniak, C. (2012). Equation of State for a Complex Plasma from Recursive Bayesian Estimation. Phys. Rev. Lett., 111 015002.
Ralph, J., Oxtoby, N. (2012). Quantum filtering one bit at a time.
Oxtoby, N., Ralph, J., Durniak, C., Samsonov, D. (2012). Target tracking in a dusty plasma: phase transitions and equations of state.
Oxtoby, N.P., Ralph, J.F., Durniak, C., Samsonov, D. (2012). Tracking shocked dust: State estimation for a complex plasma during a shock wave. Physics of Plasmas, 19 013708. doi:10.1063/1.3678201

2011

Oxtoby, N.P., Ralph, J.F., Durniak, C., Samsonov, D. (2011). Interacting Multiple Model estimators for tracking thousands of interacting, small targets in a complex plasma.
Oxtoby, N., Ralph, J.F., Durniak, C., Samsonov, D. (2011). Myriad target tracking in a dusty plasma..
Samsonov, D., Durniak, C., Harvey, P., Hall, E., Oxtoby, N., Ralph, J., ...Morfill, G. (2011). Nonlinear waves and inelastic effects in complex plasmas. APS, 53 YP9-063.
Ralph, J.F., Oxtoby, N.P. (2011). Quantum Filtering One Bit at a Time. Phys. Rev. Lett., 107 260503. doi:10.1103/PhysRevLett.107.260503
Davies, J.M., Ralph, J.F., Oxtoby, N.P. (2011). Tracking System to Maximize the Engagement Envelope of a Data Linked Weapon.
Oxtoby, N.P., Ralph, J.F., Durniak, C., Samsonov, D. (2011). Visualizing a Dusty Plasma Shock Wave via Interacting Multiple-Model Mode Probabilities. Plasma Science, IEEE Transactions on, 39 2772-2773. doi:10.1109/TPS.2011.2155101

2010

Durniak, C., Samsonov, D., Oxtoby, N.P., Ralph, J.F. (2010). Molecular Dynamics Simulations of Dynamic Phenomena in Complex Plasmas. (to appear) IEEE TRANSACTIONS ON PLASMA SCIENCE, 6
Oxtoby, N.P., Ralph, J.F., Samsonov, D., Durniak, C. (2010). Tracking interacting dust: comparison of tracking and state estimation techniques for dusty plasmas.

2009

Oxtoby, N.P., Rivas, Á., Huelga, S.F., Fazio, R. (2009). Probing a composite spin-boson environment. New Journal of Physics, 11 063028.
Rivas, Á., Oxtoby, N.P., Fazio, R., Huelga, S.F. (2009). Probing a composite spin-boson environment.
Rivas, Á., Oxtoby, N., Huelga, S. (2009). Stochastic Resonance phenomena in spin chains. The European Physical Journal B - Condensed Matter and Complex Systems, 69 51-57. doi:10.1140/epjb/e2009-00108-5

2008

Oxtoby, N.P., Gambetta, J., Wiseman, H.M. (2008). Model for monitoring of a charge qubit using a radio-frequency quantum point contact including experimental imperfections. Phys. Rev. B, 77 125304.

2007

Oxtoby, N.P., Gambetta, J., Wiseman, H.M. (2007). Realistic monitoring of a charge qubit using a radio-frequency quantum point contact. .

2006

Oxtoby, N.P., Wiseman, H.M., Sun, H.-.B. (2006). Semiconductors II: Surfaces, interfaces, microstructures, and related topics-Sensitivity and back action in charge qubit measurements by a strongly coupled single-electron transistor. Physical Review-Section B-Condensed Matter, 74 45328.
Oxtoby, N.P., Wiseman, H.M., Sun, H.-.B. (2006). Sensitivity and back action in charge qubit measurements by a strongly coupled single-electron transistor. Phys. Rev. B, 74 045328. doi:10.1103/PhysRevB.74.045328

2005

Oxtoby, N.P., Warszawski, P., Wiseman, H.M., Sun, H.-.B., Polkinghorne, R.E.S. (2005). Quantum trajectories for the realistic measurment of a solid-state charge qubit. Phys. Rev. B, 71 165317.
Oxtoby, N.P., Warszawski, P., Wiseman, H.M., Sun, H.-.B., Polkinghorne, R.E.S. (2005). Semiconductors II: Surfaces, interfaces, microstructures, and related topics-Quantum trajectories for the realistic measurement of a solid-state charge qubit. Physical Review-Section B-Condensed Matter, 71 165317.

2003

Oxtoby, N., Sun, H.B., Wiseman, H.M. (2003). Noise in detection of qubit states using a quantum point contact.
Oxtoby, N.P., Sun, H.-.B., Wiseman, H.M. (2003). Non-ideal monitoring of a qubit state using a quantum tunnelling device. J. Phys.: Condens. Matter, 15 8055-8064.

1900

Oxtoby, N.P. (1900). "Keeping it real": A quantum trajectory approach to realistic measurement of solid-state quantum systems. (Doctoral Dissertation). Griffith University.
Xu, M.-.C., Zhou, Y.-.K., Jin, C., Blumberg, S.B., Wilson, F.J., Groot, M.D., ...Jacob, J. (1900). MisMatch: Learning to Change Predictive Confidences with Attention for Consistency-Based, Semi-Supervised Medical Image Segmentation.
Young, A.L., Oxtoby, N.P., Daga, P., Cash, D.M., Fox, N., Ourselin, S., ...Alexander, D.C. (1900). MONDAY, JULY 14, 2014 ORAL SESSIONS O2-05 BIOMARKERS: MULTI-MODAL COMPARISONS O2-05-01 A DATA-DRIVEN MODEL OF BIOMARKER.
Oxtoby, N.P., Shand, C., Cash, D.M., Alexander, D.C., Barkhof, F. (1900). Targeted screening for Alzheimer’s disease clinical trials using data-driven disease progression models. Cold Spring Harbor Laboratory.
Marinescu, R.V., Oxtoby, N.P., Young, A.L., Bron, E.E., Toga, A.W., Weiner, M.W., ...Toni, T. (1900). The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up. Machine Learning for Biomedical Imaging (MELBA), Dec 2021,