4 citations · 13 across the 6 of their papers we have counts for
6 papers
Designing A Clinically Applicable Deep Recurrent Model to Identify Neuropsychiatric Symptoms in People Living with Dementia Using In-Home Monitoring Data
Francesca Palermo, Honglin Li, Alexander Capstick +6
Agitation is one of the neuropsychiatric symptoms with high prevalence in dementia which can negatively impact the Activities of Daily Living (ADL) and the independence of individu…
Semi-supervised Learning for Identifying the Likelihood of Agitation in People with Dementia
Roonak Rezvani, Samaneh Kouchaki, Ramin Nilforooshan +2
Interpreting the environmental, behavioural and psychological data from in-home sensory observations and measurements can provide valuable insights into the health and well-being o…
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation
Sebastian G. Popescu, David J. Sharp, James H. Cole +2
We propose a parameter efficient Bayesian layer for hierarchical convolutional Gaussian Processes that incorporates Gaussian Processes operating in Wasserstein-2 space to reliably…
An attention model to analyse the risk of agitation and urinary tract infections in people with dementia
Honglin Li, Roonak Rezvani, Magdalena Anita Kolanko +5
Behavioural symptoms and urinary tract infections (UTI) are among the most common problems faced by people with dementia. One of the key challenges in the management of these condi…
Deep Representation for Connected Health: Semi-supervised Learning for Analysing the Risk of Urinary Tract Infections in People with Dementia
Honglin Li, Magdalena Anita Kolanko, Shirin Enshaeifar +13
Machine learning techniques combined with in-home monitoring technologies provide a unique opportunity to automate diagnosis and early detection of adverse health conditions in lon…
Hierarchical Gaussian Processes with Wasserstein-2 Kernels
Sebastian Popescu, David Sharp, James Cole +1
Stacking Gaussian Processes severely diminishes the model's ability to detect outliers, which when combined with non-zero mean functions, further extrapolates low non-parametric va…