Psychologists, mathematicians and data scientists at the University of Sydney are teaming up to investigate how artificial intelligence (AI) and machine learning technologies can guide effective support and treatment for people with neurological disease and mental health disorders.
The two multidisciplinary projects received more than $7 million federal funding to focus on using AI to develop technology to support youth mental health care and to build an extensive AI network for more accurate diagnosis of neurological disorders such as multiple sclerosis.
Both projects are led by the University of Sydney’s Brain and Mind Centre.
The investment into Sydney-led research was announced by the Minister for Health, the Hon Greg Hunt MP as part of the Australian Government’s Medical Research Future Fund (MRFF).
Co-Director and head of Translational Research at the Brain and Mind Centre, Professor Matthew Kiernan, said: “The Brain and Mind Centre asks big questions for real-world outcomes. These research programs are based on patient-centred questions, and as such, they draw on collaborations across academic disciplines, health providers and industry partners who bring a unique depth of knowledge to each program.”
An AI ecosystem to set benchmark for disease diagnosis
Professor Michael Barnett, together with the Sydney Neuroimaging Analysis Centre (SNAC) will lead a project awarded $4.02 million to investigate how AI can be paired with medical imaging technologies to set a new standard for the diagnosis, monitoring and treatment of neurological disease.
The Translating AI Networks to Support Clinical Excellence in Neuro Diseases (TRANSCEND) project will build a new, hybrid AI learning ecosystem by training it to recognise biomarkers linked to disease progression of the common, disabling neurological condition, multiple sclerosis.
The project is a collaboration between the University of Sydney, industry specialists in medical imaging and health provider networks.
Professor Barnett, Head of Computational Neuroscience Team at the Brain and Mind Centre, said TRANSCEND fills an important research gap of the future of AI technologies to transform the health sector.
“Software-generated ‘artificial neural networks’ have demonstrated a remarkable capacity for (generic) image recognition. 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 access to real-world data.”
“By incorporating real-world data, TRANSCEND will enable new AI research and technologies within the health sector, while preserving patient privacy and data security.”
Guiding mental health care with AI
Dr Frank Iorfino, research fellow in youth mental health and technology at the Brain and Mind Centre and Faculty of Medicine and Health is leading a project using AI to test and quantify the impacts of youth mental health interventions.
Leading the methods and modelling component of the project is statistician Professor Sally Cripps, director of the University of Sydney Centre for Translational Data Science and the ARC Industrial Transformation Training Centre for Data Analytics for Resources and Environments.
The project has been awarded more than $3.1 million.
The study will bring together data and computer scientists, who will work alongside clinicians and health services to develop digital tools that can guide clinical decisions about the appropriate interventions and treatments for young people who seek mental health care.
“Mental disorders are the leading cause of disability and death among young people,” said Dr Iorfino.
“A key challenge for youth mental health care is how to make effective clinical decisions about the timing and sequence of interventions, particularly for those with complex needs. This three-year project will use AI to model youth mental health outcomes and quantify the impact of interventions on these outcomes.”
Brain and Mind Centre Co-Director, Youth Mental Health and Policy, Professor Ian Hickie, said: “From a clinical perspective, these new approaches could result in real-time decision aids that would help us to make much more accurate decisions about which early interventions are of greatest benefit to young people with emerging major mood or psychotic disorders. They will also guide our efforts to provide the most effective forms of secondary prevention. “