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We demonstrate the use of a probabilistic generative model to explore the biomarker changes occurring as Alzheimer's disease develops and progresses. We enhanced the recently introduced event-based model for use with a multi-modal sporadic disease data set. This allows us to determine the sequence in which Alzheimer's disease biomarkers become abnormal(More)
In this paper we propose a novel algorithm which leverages models of white matter fibre dispersion to improve tractography. Tractography methods exploit directional information from diffusion weighted magnetic resonance (DW-MR) imaging to infer connectivity between different brain regions. Most tractography methods use a single direction (e.g. the principal(More)
The event-based model constructs a discrete picture of disease progression from cross-sectional data sets, with each event corresponding to a new biomarker becoming abnormal. However, it relies on the assumption that all subjects follow a single event sequence. This is a major simplification for sporadic disease data sets, which are highly heterogeneous,(More)
In this Letter we consider the purification of a quantum state using the information obtained from a continuous measurement record, where the classical measurement record is digitized to a single bit per measurement after the measurements have been made. Analysis indicates that efficient and reliable state purification is achievable for one- and two-qubit(More)
We present a framework for simulating cross-sectional or longitudinal biomarker data sets from neurodegenerative disease cohorts that reflect the temporal evolution of the disease and population diversity. The simulation system provides a mechanism for evaluating the performance of data-driven models of disease progression, which bring together biomarker(More)
PURPOSE OF REVIEW This article argues that the time is approaching for data-driven disease modelling to take centre stage in the study and management of neurodegenerative disease. The snowstorm of data now available to the clinician defies qualitative evaluation; the heterogeneity of data types complicates integration through traditional statistical(More)
In a laboratory, a two-dimensional complex (dusty) plasma consists of a low-density ionized gas containing a confined suspension of Yukawa-coupled plastic microspheres. For an initial crystal-like form, we report ideal gas behavior in this strongly coupled system during shock-wave experiments. This evidence supports the use of the ideal gas law as the(More)
Tracking myriad (thousands of) interacting dust particle targets in a complex (dusty) plasma is considered. Multiple extended-Kalman-filter-based trackers were deployed on target subsets of various sizes, with track data fusion performed offline. Filter-based tracking was more accurate than particle tracking velocimetry, particularly for estimates of target(More)