Novel pathways toward improving relapse prediction in schizophrenia

Funding Activity

Website
http://purl.org/au-research/grants/nhmrc/GNT1142424

Funding Status
Closed

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Funded Activity Summary

Relapse is a devastating problem in schizophrenia and our ability to predict when it occurs is still relatively poor. This project seeks to investigate a new method of tracking relapse by measuring speech and symptom changes across time. This novel design is supported by advanced data modelling methods to provide sensitive predictive ability. This project has the potential to significantly improve relapse prediction in schizophrenia and so support and increase beneficial outcomes for patients

Funded Activity Details

Start Date: 01-01-2018

End Date: 01-01-2021

Funding Scheme: Early Career Fellowships

Funding Amount: $318,768.00

Funder: National Health and Medical Research Council

Research Topics

ANZSRC Field of Research (FoR)

Medical and Health Sciences not elsewhere classified

ANZSRC Socio-Economic Objective (SEO)

There are no SEO codes available for this funding activity

Other Keywords

data analysis | longitudinal study | relapse prevention | schizophrenia | speech

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