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Grant Award View - GA89123
Explainable machine learning to improveyouth mental health care
GA ID:
GA89123
Agency:
Department of Health and Aged Care
Approval Date:
17-Jun-2020
Publish Date:
26-Jun-2020
Category:
Academic Medical Research
Grant Term:
25-Jun-2020 to 6-Dec-2023
Value (AUD):
$3,107,627.00
(GST inclusive where applicable)
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
DoHAC 19/20 Health Policy Research and Analysis
Grant Program:
Medical Research Future Fund
Grant Activity:
Explainable machine learning to improveyouth mental health care
Purpose:
Mental disorders are the leading cause of disability and death among young people. A key challenge for mental health care is to develop new tools that are useful for guiding clinical decisions about the appropriate interventions for individual’s presenting for care. This project will: (i) use explainable machine learning and simulation to infer the causal relationship between mental health outcomes over time; (ii) use dynamic simulation modelling to test and probabilistically quantify the impacts of interventions on outcomes; and (iii) co–design an ethical clinical decision–support tool that identifies how to target assessment and interventions to optimise outcomes for individuals presenting to health services.
GO ID:
GO Title:
MRFF - National Critical Research Infrastructure Initiative: 2019 Applied Artificial Intelligence Research in Health
Internal Reference ID:
MRFAI000097
Selection Process:
Open Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
UNIVERSITY OF SYDNEY
Recipient ABN:
15 211 513 464
Grant Recipient Location
Suburb:
CAMPERDOWN
Town/City:
CAMPERDOWN
Postcode:
2006
State/Territory:
NSW
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
NSW
Postcode:
2050
Country:
AUSTRALIA