Application of machine learning techniques to disease surveillance to identify risk groups for blood borne viruses and sexually transmissible infections

Funding Activity

Website
http://purl.org/au-research/grants/nhmrc/2005418

Funding Status
Status not available

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Funded Activity Summary

Electronic medical records from general practice are used to provide clinically detailed disease surveillance data to inform public health decisions. Risk factor information is not systematically recorded making it difficult to identify risk groups using these data. This PhD will improve surveillance by applying new data science methods to de-identified electronic medical records from general practice to better identify risk groups for blood borne viruses and sexually transmissible infections.

Funded Activity Details

Start Date: 01-01-2020

End Date: End date not available

Funding Scheme: Postgraduate Scholarships

Funding Amount: $76,365.00

Funder: National Health and Medical Research Council

Research Topics

ANZSRC Field of Research (FoR)

ANZSRC Socio-Economic Objective (SEO)

There are no SEO codes available for this funding activity

Other Keywords

health informatics | health surveillance | information science/medical informatics | population health

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