HDR UK Site
Using our machine learning approach for antimicrobial prediction as a test case, we will use theoretical and numerical methods to investigate mechanisms of failure, which has wider implications for the use of AI in public health.
- Develop a basic framework to assess the accuracy of AI predictions.
- Present findings in a user-friendly manner to aid the inclusion of AI predictions in public-health/medicine.
- Test the approach on a small focus group.
Expand the methodology to other settings (requires additional data).
Project Team / Collaborators
Generating research-ready, actionable, real-time and large-scale insights
29 September 2022 at 3:00 pm
Professor Richard Dobson will present on Generating research-ready, actionable, real-time and large-scale insights from routinely collected, unstructured (e.g. letters, notes, reports) as well...
DaC-VaP-2 National Data Assets & Opportunities for Collaboration
22 September 2022 at 1:55 pm
The DaC-VaP-2 project webinar is being held thanks to the funding and support of BREATHE, Health Data Research UK and The Alan Turing Institute. In this webinar chaired by Professor Aziz Sheikh,...
Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study
4 October 2022 at 3:00 pm
As part of the HDR UK Applied Analytics seminar series Dr Alasdair Henderson will present on Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a...