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
R for Health Data Science: from clinicians who code to Shiny interventions
27 May 2022 at 10:00 am
Riinu Pius will present on R for Health Data Science: from clinicians who code to Shiny interventions on Friday 27th May at 10:00 UK time. Please click here for more details and to register.
Mapping multimorbidity in individuals with schizophrenia and bipolar disorders: evidence from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register
21 April 2022
People with severe mental illness, such as schizophrenia spectrum disorders or bipolar disorders, have higher death rates. It is difficult to study mental health records at scale, so a team of...
Evaluation of the ASSIGN open-source deterministic address-matching algorithm for allocating unique property reference numbers to general practitioner-recorded patient addresses
20 April 2022
Being able to link addresses across systems offers a valuable resource for health data science. However, they are often not standardised despite a government push towards this. Researchers at the...