There is a problem with one of the content items on this page. The affected component type is:

Staff Profile Main Details

The system reports the following message:

No records found

Areas of Expertise

  • Population Health Research
  • SAIL Databank
  • Data Linkage
  • SQL
  • R
  • GIS
  • Spatial Data Analysis


  1. Hurt, L., Wright, M., Demmler, J., VanDerVoort, J., Morris, S., Brook, F., Tucker, D., Chapman, M., Francis, N., Daniel, R., Fone, D., Brophy, S., Paranjothy, S. Mild-to-moderate renal pelvis dilatation identified during pregnancy and hospital admissions in childhood: An electronic birth cohort study in Wales, UK PLOS Medicine 16 7 e1002859
  2. Demmler, J., Brophy, S., Marchant, A., John, A., Tan, J. Shining the light on eating disorders, incidence, prognosis and profiling of patients in primary and secondary care: national data linkage study The British Journal of Psychiatry 216 2 105 112
  3. Hurt, L., Wright, M., Brophy, S., Demmler, J., Paranjothy, S. Association of hospital admission for renal causes during childhood with renal pelvis dilatation identified during pregnancy: a prospective electronic birth cohort study The Lancet 392 S44
  4. Gabbe, B., Dipnall, J., Lynch, J., Rivara, F., Lyons, R., Ameratunga, S., Brussoni, M., Lecky, F., Bradley, C., Simpson, P., Beck, B., Demmler, J., Lyons, J., Schneeberg, A., Harrison, J. Validating injury burden estimates using population birth cohorts and longitudinal cohort studies of injury outcomes: the VIBES-Junior study protocol BMJ Open 8 8 e024755
  5. Demmler, J., Brophy, S., Hill, R., Rahman, M., Bandyopadhyay, A., Healy, M., Paranjothy, S., Murphy, S., Fletcher, A., Hewitt, G., John, A., Lyons, R. Educational Attainment at Age 10–11 Years Predicts Health Risk Behaviors and Injury Risk During Adolescence Journal of Adolescent Health 61 2 212 218

See more...


  • PMIM01 Scientific Computing and Healthcare

    The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate. Module leader is Dan Thayer

  • PMIM02 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. Module leader is Dr Joanne Demmler