A group of research labs in Adelaide, South Australia has recently begun using a wealth of health data provided by SA Pathology to determine ways to use Artificial intelligence (AI) to identify health issues in high-risk patients before they happen.
Based at the Royal Adelaide Hospital, they teamed with the Australian Institute for Machine Learning, the MIT bigdata Living Lab at Lot Fourteen innovation precinct and the Australian Research Centre for Interactive and Virtual Environments at the University of South Australia.
They are developing new systems with AI for preventative care and other health issues.
SA Pathology anticipates using AI will improve preventative health care, speed up some manual, time-consuming tasks and lower costs to deliver better public health outcomes.
Dr. Zhibin Liao, a machine learning researcher with AIML, is among the team working with SA Pathology to determine how machine learning can work in preventative healthcare.
Dr. Liao said one of the benefits of working with SA Pathology is that the organization has a rich, globally unique data set, having performed more than 42 million tests in the past three financial years that complements more than 80 years of historical pathology data.
“They have data for many years, so we can analyze population data over a long period.”
“And it’s continuous unless people move interstate. We can look at blood tests that show early signs of pre-diabetes, and if there are patterns and trends in certain geographic hotspots, it means doctors in those areas can get an early warning about what to focus on.”
Technology to assist doctors with simple tasks
Using AI in pathology, the software can alert doctors when their patients forget to get important tests or if a patient is at higher risk of requiring hospitalization in the future.
“If you can do a GP visit and find the problem earlier, for the patient it’s much better to prevent them being hospitalized,” Dr. Liao said.
SA Pathology interim executive director, Lucas Semmler, said the organization is looking at three key areas which include clinical decision making, disease surveillance and population health management so as to drive improved outcomes for the population.
“There are unnecessary hospitalizations, through compliance or chronic diseases or how patients manage their health and how they are managed in the GP sector,” Semmler said.
“It’s about leveraging that to assist in reducing the overall burden on the health system.
“There’s data in the pathology sector and the broader health sector where applying AI will be critical to meeting the needs of the time and actually addressing key issues early.”
“AI is going to be part of the everyday, normal workload and work practices in the future.”
Health proceedures will still be manned by humans
“There’s always going to be a scientist or a pathologist in the background because AI will only take you to a certain level, but there are significant volumes of data to go through.”
“We are working across the public health sector, as well as partnering with GPs in the primary health care system, to look at where pathology in the context of the broader health sector can drive some of those improvements to the state and delivery of services.”
Australian Institute for Machine Learning is ranked as second globally for computer vision.
Being part of the University of Adelaide, it’s working with the MIT bigdata Living Lab to ensure the project is delivered with world best practices for privacy, data security and ethics in AI.
Both research labs are based in the innovation district of Lot Fourteen in the heart of Adelaide.
