Artificial Intelligence and Cyber Futures Institute
Artificial Intelligence and Cyber Futures Institute
The AI and Cyber Futures Institute is establishing a robust cross-disciplinary capability in AI and digital health technology, positioning ourselves at the forefront of digital health innovation.
Our AI and Digital Health Technology Program is developing and applying cutting-edge computational models, AI-enabled diagnostic and monitoring devices, clinical informatics, bioinformatics capacity, and interdisciplinary research to improve healthcare systems and outcomes.
Collaborating with industry and clinical partners, we are leveraging deep-learning and large language models to create predictive models for various diseases and clinical challenges.
This program features a dynamic team utilising both expertise and capability from the AI and Cyber Futures Institute and Rural Health Research Institute.
Below outlines the key focuses and projects that the AI and Digital Health Technology Program is addressing. Further health related projects can be found in the 'Sustainable Behaviours' research stream.
Project 1: Developing multimodal large language models for monitoring brain functions and disorders utilizing EEG, fMRI, MRI, and questionnaire (e.g., clinical report) information.
Project 2: Developing large language models for generating personal health trajectories utilising extensive health data.
Project 3: Predicting the adverse pregnancy and birth outcomes (e.g., Preterm birth, low birth weight, Neurodevelopmental disorders) utilising clinical and blood based genetic biomarkers at early-stage pregnancy.
Project 4: AI-Empowered Screening of Children with ASD to Enable Tailored Clinical Interventions
Project 1: Developing Deep Learning models for the automated diagnosis of stroke utilising imaging data.
Project 2: Identification of Blood-Based Genetic Biomarkers for Stroke Diagnosis.
Project 3: Developing AI-enabled portable ECG devices for the diagnosis of myocardial infarction.
Project 4: Developing AI-enabled portable EEG devices for the diagnosis of mental health conditions (e.g., major depression).
Project 1: Developing machine learning models for public health and clinical data.
