AIH focuses on developing knowledge representation and machine learning platforms to support knowledge discovery from healthcare data. AIH is also involved in the development of multi-agent platforms to support healthcare delivery and e-health infrastructures.
A distributed multi-agent environment for connecting patients with their carers outside the hospital environment and enabling data collection for research. APPROaCh automates the process of collecting standardised patient-provided outcome measures (PROMs) via a reward-based environment.
Using principles of qualitative temporal reasoning, EQsPERt models longitudinal patient records as graphs of temporally-connected events. EQsPERt feeds these graphs as input to learning frameworks to detect and predict patterns of similarities between patients with similar phenotypes.
There is an increase in drug abusers resorting to injecting into the femoral artery (groin). Anecdotal evidence, found by Professor John Strang, has shown that those injectors who receive an ultrasound scan and are shown the image are more likely to stop injecting.