The bi-annual CAMO-Net UK meeting took place this week, focusing on applying artificial intelligence (AI) driven solutions to optimise infectious disease management and antimicrobial use. Bringing together cutting-edge research and collaborative insights, the event highlighted the transformative potential of machine learning and data-driven innovation in tackling some of the most pressing global health challenges.
CAMO-Net UK is made up of teams from the University of Liverpool and Imperial College London. The teams meet in-person twice a year to foster collaboration between the sites.
The day began with a welcome from CAMO-Net lead Professor Alison Holmes, who discussed the importance of harnessing the power of data to address antimicrobial resistance. “AI is a highly prominent and important area, and our teams across Liverpool and London are working at the forefront of using these innovations to optimise antimicrobial use. CAMO-Net provides an invaluable platform for collaboration and mutual learning in this vital field.”
Key presentations at the workshop featured Dr Alessandro Gerada from the University of Liverpool, who explained how Escherichia coli genome data predicts antimicrobial minimum inhibitory concentrations, potentially improving the accuracy and speed of treatment decisions. Liverpool’s Dr Yinzheng Zhong built on this, showcasing a scalable machine learning model for antimicrobial susceptibility predictions. Imperial College London PhD student Oskar Fraser-Krauss also introduced a dynamic graph-based machine learning approach for early outbreak detection of antimicrobial resistance. These projects reinforced the potential of using data-driven approaches.
The teams from Liverpool and London discussed data mapping and goal alignment on upcoming CAMO-Net research projects. These sessions fostered further collaboration and set the stage for the next steps in CAMO-Net UK’s AI-driven initiatives.
The meetings concluded with networking and informal discussions, reinforcing the collaborative spirit that underpins CAMO-Net’s mission. CAMO-Net is committed to leveraging AI and data-driven solutions to address antimicrobial resistance in humans and enhance infectious disease management.
