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Deep datasets push Australia to AI frontline of predictive health

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Research labs in Adelaide, South Australia, are using health data to determine how Artificial Intelligence (AI) can be used to identify health issues in high-risk patients.

Based at the Royal Adelaide Hospital, SA Pathology has teamed with the Australian Institute for Machine Learning (AIML) and the MIT bigdata Living Lab at Lot Fourteen innovation precinct, as well as the Australian Research Centre for Interactive and Virtual Environments at the University of South Australia.

Since teaming up in July, they have been developing new systems based around AI for preventative care and other health industry 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, said Using AI in pathology, software can be built to alert doctors when their patients are forgetting to get their important tests, or if a patient is at higher risk of requiring hospitalisation in the future.

“They have data for many years, so we can analyse population data over a long period. And it’s continuous, unless people move interstate,” Dr Liao said.

“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.

“If you can do a GP visit, and find the problem earlier, for the patient it’s much better to prevent them being hospitalised.”

SA Pathology interim executive director, Lucas Semmler, said the organisation is looking at three key areas: clinical decision making, disease surveillance and population health management to drive improved outcomes for the population.

“We know there are unnecessary hospitalisations, through compliance or chronic diseases or how patients manage their own health and how they are managed within the GP sector,” Semmler said.

“It’s about leveraging that and how we can assist in that space to reduce the overall burden on the health system.

“There’s significant information within the pathology sector, and the broader health sector as well, where applying AI is going to be critical to meeting the needs of the time and actually addressing key issues early.”

Semmler said AI technology is going to ‘become part of the everyday, normal workload and work practices in the future’.

“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,” Semmler said.

“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.”

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