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Optimising surveillance and treatment of infectious diseases using AI and Big Data

Project

Optimising surveillance and treatment of infectious diseases using AI and Big Data

Project Details

Infections pose a major risk to health globally. Antimicrobial resistance (AMR) threatens effective treatment of infection and healthcare associated infections (HCAIs) impact more than 10% of all hospital patients.

Advances in data availability and new artificial intelligence (AI) methods offer the chance to develop:
 

  • More responsive, comprehensive, and automated HCAI/AMR surveillance generating better breadth and depth of intelligence to drive action and changes in practice to protect diverse populations at local, regional, and national levels.
  • Predictive tools to improve care of individual patients and combat AMR.
  • Methods, infrastructure and skills to optimally use rapidly-evolving electronic healthcare record and patient-contributed data, and emerging AI technologies. 

Several possible projects are available, including:
 

  • Developing/testing automated electronic surveillance approaches for rapidly detecting changes in infections and identifying at-risk populations; and deploying these tools in hospitals and national systems
  • Extending and piloting in hospitals predictions of personal AMR risk to optimise infection treatment, prevention and control, developing generalisable methods that can update over time/to new locations, and approaches for safely implementing them
  • Pre-emptive surveillance, investigating which metrics of hospital processes (e.g. isolation/screening/diagnostic use/cleaning) are associated with HCAI/AMR to inform prevention
Category
Epidemiology
University
7
Project Listed Date
UK Mentor

Prof. David Eyre

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