David J. Sharp

Automatic lesion analysis for increased efficiency in outcome prediction of traumatic brain injury

The accurate prognosis for traumatic brain injury (TBI) patients is difficult yet essential to inform therapy, patient management, and long-term after-care. Patient characteristics such as age,...

Distributional Gaussian Processes Layers for Out-of-Distribution Detection

Machine learning models deployed on medical imaging tasks must be equipped with out-of-distribution detection capabilities in order to avoid erroneous predictions. It is unsure whether...

Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation

We propose a parameter efficient Bayesian layer for hierarchical convolutional Gaussian Processes that incorporates Gaussian Processes operating in Wasserstein-2 space to reliably propagate...

An attention model to analyse the risk of agitation and urinary tract infections in people with dementia

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 conditions is early...

Inference of functional connectivity from structural brain connectivity

Exploiting hierarchy in structural brain networks

Inference of functional connectivity from direct and indirect structural brain connections

Automated Microscopy Screen to Identify Components Required for Mitotic Cell Cycle Progression in Human Cells

Implicit Gaussian process representation of vector fields over arbitrary latent manifolds

Relating Brain Functional Connectivity to Anatomical Connections: Model Selection

Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization

A Digital Platform for Remote Healthcare Monitoring

Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation

A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections

Hierarchy in structural brain networks

Automatic Lesion Analysis for Increased Efficiency in Outcome Prediction of Traumatic Brain Injury

Identifying Household Fingerprint Using Intelligent Passive Monitoring for People Living with Dementia

Deep Representation for Connected Health: Semi-supervised Learning for Analysing the Risk of Urinary Tract Infections in People with Dementia

Machine learning techniques combined with in-home monitoring technologies provide a unique opportunity to automate diagnosis and early detection of adverse health conditions in long-term...