Predicting Fracture Outcomes From Clinical Registry Data Using Artificial Intelligence Supplemented Models For Evidence-informed Treatment (PRAISE) Study
Funder
National Health and Medical Research Council
Funding Amount
$636,217.00
Summary
This project will establish the role of artificial intelligence (AI) techniques to improve the prediction of clinical and longer-term patient reported outcomes following wrist fracture. Prediction models based on existing, routinely collected registry data with will be compared with models based on registry data enhanced by AI analysis of X-ray images, radiology reports and surgical reports. The AI analysis will reason on both image and text data, better replicating how humans learn.
Functional Effects Of Polymorphic Variation Of The Aromatase (CYP19) Gene On Enzyme Activity:relationship To Disease
Funder
National Health and Medical Research Council
Funding Amount
$237,708.00
Summary
After menopause, oestrogen synthesis changes from an ovarian to an adipose source by concersion of androgens to estrogens, a process catalyzed by aromatase, the product of the CYP19 gene. We will generate mutants of the CYP19 gene that we have previously found in humans by site-directed mutagenesis and observe the effects of these mutants on aromatase function. This research will help with diagnosis and treatment of breast and other cancers and osteoporosis in humans .
Geelong Osteoporosis Study: Fracture Risk Prediction Based On Twenty Years Of Prospective Data.
Funder
National Health and Medical Research Council
Funding Amount
$1,107,758.00
Summary
In this population-based study we will generate evidence, both environmental and genetic, for defining fracture risk in Australian men and women. This will help identify individuals likely to sustain fragility fractures so that suitable therapies can be recommended. The data will be useful for developing prognostic models in both a clinical setting and for genetic screening programmes.