This is one of our CSIRO Next Generation AI graduate programme PhD projects with Future Wellness Group:
Using artificial intelligence software and unique algorithms for predictive analytics that incorporate modelling, machine learning, and data mining, we are building, analysing and modelling an individual’s baseline health profile against thousands (eventually millions) of similar people and their data points along with decades of evidence-based medical and population research.
Our previous work centered on the prediction of Diabetes Type Two – a major debilitating chronic disease that is a major contributor to death, worldwide. This work then led to understanding the extended comorbidities that surround all chronic diseases and conditions and how we might be able to provide tools that would allow individuals to understand their own personal risk at any time in their lives. We plan to offer appropriate health care strategies that combine guidance and maintenance to provide a personal health ecosystem across a lifetime.
This research is novel, innovative, challenging and rewarding with the goal of delivering predictive personal health insights for people across the world to improve their long-term health outlook.
Project Requirements and Goals
- Raise the level of personal health insights for longer and healthier lives
- Raise the level of personal health knowledge
- Reduce the volume of presentations to primary and secondary healthcare
- Reduce the level of chronic illness in our communities
- Reduce the burden of cost within healthcare medical systems
- Improve conditions and opportunities for health professionals
- Improve the quality of life for millions of people across the world
- Remove the inequality within healthcare services
Industry Partner - Future Wellness Group Holdings Pty Ltd.
FWG is an Australian technology company that has developed novel techniques and processes that predict when an individual is most likely to have a chronic condition or illness, in their future. With this knowledge we are able to offer evidence based guidance and maintenance to alter that trajectory. We are building ground breaking technology that is under constant development with enhancements, new capabilities and functionality being added regularly.
Must be domestic student - Australian or New Zealand citizen or Australian Permanent Resident
Honors or Masters degree in Software Engineering or similar
Meet H1E requirements for Monash FIT PhD entry
Interest/experience in human-centric software requirements, design, evaluation an advantage
Interest/experience in eHealth or similar software application development an advantage
Some machine learning skills an advantage