Personal Future Health Prediction

Primary supervisor

John Grundy

Co-supervisors

  • Mark Foley, Future Wellness Group

Using artificial intelligence software and unique algorithms for predictive analytics that incorporate modelling, machine learning, and data mining, we analyse, model, and build 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 focused on the prediction of Diabetes Type Two – a major debilitating chronic disease, and a significant contributor to global deaths. This work then led to an understanding of the extended co-morbidities that both link and surround all chronic diseases and conditions, and how we might provide tools to allow individuals to understand their risk at any time in their lives. We aim to deliver integrated healthcare strategies that combine personalised guidance with ongoing maintenance, fostering a lifelong, adaptive personal health ecosystem.

 


 

Student cohort

Single Semester
Double Semester

Aim/outline

This research is novel, ambitious, and deeply rewarding, driven by the goal of delivering predictive personal health insights to individuals worldwide.

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 inequality within healthcare services

 

Industry Partner - Future Wellness Group Holdings Pty Ltd:

FWG is an Australian technology company pioneering AI-driven techniques and intelligent processes that predict when an individual is most likely to develop a chronic condition or illness. This personalised foresight allows us to deliver tailored, evidence-based guidance and ongoing support, which can proactively reshape a person’s health journey. Our cutting-edge platform continually evolves, integrating new capabilities and enhancements to meet the dynamic needs required for personalised health care.

 

If interested in this project PLEASE CONTACT MARK FOLEY TO DISCUSS:  Mark Foley <mark@futurewellnessgroup.com>

    URLs/references

    https://www.futurewellnessgroup.com/

     

    Required knowledge

    • Interest/experience in human-centric software requirements, design, evaluation, and an advantage
    • Interest/experience in eHealth or similar software application development is an advantage
    • Machine learning, risk modelling and statistical experience with logistic regression, such as Bayesian networks and decision trees, etc., are an advantage