Predicting fracture outcomes from clinical Registry data using Artificial Intelligence Supplemented models for Evidence-informed treatment (PRAISE) study

Funding Activity

Website
http://purl.org/au-research/grants/nhmrc/2003537

Funding Status
Status not available

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Funded Activity 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.

Funded Activity Details

Start Date: 01-01-2020

End Date: 01-01-2013

Funding Scheme: Ideas Grants

Funding Amount: $636,217.00

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

distal radial fractures | orthopaedic surgery | outcomes research | prediction

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