Novelty detection is the task of classifying test data that differ in some respect from the data
that are available during training. This may be seen as “one-class classification”, in which a …

The majority of patients in the hospital are ambulatory and would benefit significantly from
predictive and personalized monitoring systems. Such patients are well suited to having …

Background Sleep disturbance occurs in most patients with delusions or hallucinations and
should be treated as a clinical problem in its own right. However, cognitive behavioural …

Gaussian process (GP) models are a flexible means of performing nonparametric Bayesian
regression. However, GP models in healthcare are often only used to model a single …

A polygenic risk score estimates the genetic risk of an individual for some disease or trait,
calculated by aggregating the effect of many common variants associated with the condition …

Background: Treatment of hyperglycemia in women with gestational diabetes mellitus
(GDM) is associated with improved maternal and neonatal outcomes and requires intensive …

Advances in wearable sensing and communications infrastructure have allowed the
widespread development of prototype medical devices for patient monitoring. However …

Background When using a continuous outcome measure in a randomised controlled trial
(RCT), the baseline score should be measured in addition to the post-intervention score …

Adverse hospital patient outcomes due to deterioration are often preceded by periods of
physiological deterioration that is evident in the vital signs, such as heart rate, respiratory …

Deep neural networks have been integrated into the whole clinical decision procedure
which can improve the efficiency of diagnosis and alleviate the heavy workload of …