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Grant Award View - GA83502
Novel deep learning methods for large-scale cardiovascular risk...
GA ID:
GA83502
Agency:
Department of Health and Aged Care
Approval Date:
14-May-2020
Publish Date:
15-Jun-2020
Category:
Health and Medical Research
Grant Term:
1-Jun-2020 to 31-May-2023
Value (AUD):
$1,467,090.60
(GST inclusive where applicable)
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
DoHAC 19/20 1.1 Health Policy Research and Analysis
Grant Program:
2019_MRFF_Cardiovascular_Health_2020
Grant Activity:
Novel deep learning methods for large-scale cardiovascular risk screening using Australian digital health data
Purpose:
Through two synergistic studies using routinely collected data and novel deep learning methods, we will deliver: (1) The world’s first dynamic cardiovascular risk prediction algorithm that uses clinical text data and longitudinal event sequences; and (2) The world's first mammography-derived cardiovascular risk prediction algorithm.
GO ID:
GO Title:
MRFF - Cardiovascular Health Mission - 2019 Cardiovascular Health Grant Opportunity
Internal Reference ID:
MRF1201433
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
Yes
Confidentiality Reason(s) - Contract:
Privacy Act 1988
Intellectual property
Intellectual property
Confidentiality - Outputs:
Yes
Confidentiality Reason(s) - Outputs:
Intellectual property
Grant Recipient Details
Recipient Name:
University of New South Wales
Recipient ABN:
57 195 873 179
Grant Recipient Location
Suburb:
Sydney
Town/City:
Sydney
Postcode:
2052
State/Territory:
NSW
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
ACT, NSW
Postcode:
Multiple
Country:
AUSTRALIA