Skip to main content
KBS_Icon_questionmark link-ico

 

Health (Informatics)

The Health Hub centres on computational characterisation of medically relevant study cases and data. Comprising bioinformatics, systems biology, medical and health informatics, well-being, sensors and remotely controlled robotic devices, this multidisciplinary activity not only connects academic groups within the Department of Informatics, but also links Informatics to multiple Departments, Divisions and Health Partners across the College. The overall objective is advancement in understanding fundamental mechanisms in health and disease, enabling remote diagnosis and operations, monitoring the delivery of medical practice and designing effective interventions for therapy or treatment.

Research

Key research activities in the Health hub address:

  • development of sensors for various indications, non-invasive metabolite monitoring and control for drug administration
  • development of argumentation-based models to monitor treatment concordance, assist patients to self-monitor and self-manage their treatment plans for chronic conditions, or support personalised treatment plans
  • algorithm development for learning in supervised and unsupervised biomedical data analysis, algorithms for data sharing, modelling and simulation of biological processes, sequence analysis for genomic data and health data collection via social networks
  • application of robotic technology to healthcare and medical interventions
  • development of remote tele healthcare protocols
  • development of software architectures for Learning Health Systems to deliver next-generation clinical trials and decision support systems, supporting increased transparency

Examples of impact are improvement of quality of life through:

  • remote medical diagnosis and intervention
  • affordable sensors for non-invasive monitoring
  • advancement of robotic surgery, endoscopy, prosthetics and orthotics
  • understanding of biomedical mechanisms to facilitate therapeutic intervention
  • reducing the cost of clinical research
  • improving the auditability of the research processes
  • accelerating translation of evidence into clinical practice