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Grant Award View - GA89125
Translating AI to support clinical excellence in neuro diseases
GA ID:
GA89125
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):
$4,016,415.00
(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:
Translating AI to support clinical excellence in neuro diseases
Purpose:
Software–generated 'artificial neural networks' have demonstrated a remarkable capacity for (generic) image recognition, with error rates of only 1–2%. Despite the clear potential for this technology to transform health delivery, particularly through advances in medical imaging, AI research and implementation has remained the purview of research institutes and technology companies with limited domain knowledge or access to real–world data. The project seeks to redress this imbalance by building a novel, hybrid AI learning ecosystem that links a premiere research institute (University of Sydney) and industry specialist (Sydney Neuroimaging Analysis Centre) with health provider networks (IMED Radiology and clinical Neurology partners) to generate clinically–relevant biomarkers of disease progression for the common, disabling neurological condition, multiple sclerosis. The MSBASE–XNAT imaging repository and I–MED clinical radiology site data will respectively form the key components of a unique central–federated AI learning environment, yielding algorithms that, validated in a clinical neurology environment, will set a benchmark in diagnostic MS imaging; track subclinical progression of the disease; direct therapeutic strategy; and mine hitherto untapped quantitative imaging data. The novel approach will enable new AI research and technologies within the health sector, while preserving patient privacy and data security.
GO ID:
GO Title:
MRFF - National Critical Research Infrastructure Initiative: 2019 Applied Artificial Intelligence Research in Health
Internal Reference ID:
MRFAI000085
Selection Process:
Open Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The 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