Objective The worldwide prevalence of Parkinson's disease is increasing. There is urgent
need for new tools to objectively measure the condition. Existing methods to record the …

The most popular method for computing the matrix logarithm is the inverse scaling and squaring
method, which is the basis of the recent algorithm of Al-Mohy and Higham [SIAM J. Sci. …

A current trend in high-performance computing is to decompose a large linear algebra problem
into batches containing thousands of smaller problems, that can be solved independently…

Introduction: We describe the creation of a deep neural network architecture to classify
cardiac abnormality from 12 lead ECGs. The model was created by the team “between a ROC …

We use a unique dataset to identify the key members of a football team. The methodology
uses a statistical model to determine the difficulty of a pass from one player to another, and …

Background Slowness of movement, known as bradykinesia, is the core clinical sign of
Parkinson's and fundamental to its diagnosis. Clinicians commonly assess bradykinesia by …

The recent version of the Parallel Linear Algebra Software for Multicore Architectures (PLASMA)
library is based on tasks with dependencies from the OpenMP standard. The main …

Background Computer vision can measure movement from video without the time and access
limitations of hospital accelerometry/electromyography or the requirement to hold or strap …

Objective Estimating survival can aid care planning, but the use of absolute survival projections
can be challenging for patients and clinicians to contextualise. We aimed to define how …

Cardiac abnormality detection from Electrocardiogram (ECG) signals is a common task for
cardiologists. To facilitate efficient and objective detection, automated ECG classification by …