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Utilising AI-based techniques to improve mental health treatment


To deliver AI-based adaptive trial methods to discover the most effective treatments for mental illnesses


Assisting clinicians, patients and health services to make better treatment decisions through precision medicine is a core priority for mental health

Research Partners

  • Black Dog Institute
  • University of New South Wales

25% of Australian university students experience severe psychological distress during their studies.

Consequently, many drop out of study or go on to develop more severe psychiatric disorders in their peak years. These disorders result in years of disability and lost opportunity without timely intervention.

The ‘gold standard’ method for exploring questions about which treatments to use is the randomised controlled trial (RCT). Although key for testing efficacy, comparing multiple treatment options using RCTs is time consuming, expensive, and inefficient. These challenges underline the importance of looking for new ways to explore treatment efficacy while preserving the rigour of a traditional RCT.


Our Medical Research Future Fund (MRFF) project is investigating the potential of Artificial Intelligence (AI) and adaptive trial methods to discover the most effective treatments to determine which treatment works best and for whom.

Consistent with the goals of the MRFF-AI scheme, the techniques developed as part of this project aim to be transformative, with practical applications to significant topical problems in psychiatry, such as the right choice of medication for use in depression. Beyond psychiatry, it has the potential to guide clinical decision-making in neurological and substance abuse disorders where treatment choices are uncertain.

This project also has a goal of ensuring the work is translational and that findings will transfer to practice and into policy, and will be driven by the priorities and voices of those with lived experience of mental health disorders.

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