Numbers key to suicide risk
THE potential of “big data crunching” is just beginning to be understood, but a groundbreaking project at Deakin University is set to make a major difference to mental health patients in the Geelong region.
Using number crunching, a league away from previous methods, researchers are using artificial intelligence to more accurately predict the mental health patients most at risk of suicide in the region.
Deakin’s Centre for Pattern Recognition and Data Analytics (PRaDA) director Professor Svetha Venkatesh, a world expert in big data pattern recognition, research leader Dr Truyen Tran and their team have been working with Barwon Health on the project for more than two years.
Using hospital electronic records for patients with a mental illness, their program is able to analyse large of chunks of data and is three times more accurate than previous risk detection systems.
It has been estimated 80-90 per cent of people who commit suicide have a mental illness.
“Our Health Analytics program was able to take into ac- count extensive data from electronic medical records for each of the 9000 patients from the mental health cohort of Barwon Health,” Prof Venkatesh said. “From this data, it identified patterns that showed those most at risk.
“In contrast, the manual risk assessments that are usually made by medical practitioners consider around 17 factors, categorising patients as high, medium or low risk.
“Until now, it would have been impossible to analyse this much data and discover patterns in the risk factors.”
Factors considered ranged from patient history of emergency attendance to the types of injuries they were admitted for.
The PRaDA program is being tested by Barwon Health, providing a complete risk profile for each patient with a mental illness and enabling practitioners to view the risk-relevant patient information more effectively.
“It is allowing better resource utilisation, providing support where it’s needed most and it should, hopefully, help reduce the incidence of suicide in the region,” Prof Venkatesh said.
She said the program could be adopted by health systems across Australia and overseas.
PRaDA is one of Australia’s leading research centres in the field of machine learning and pattern recognition, with researchers developing programs that analyse large-scale data patterns in areas as diverse as surveillance, social media and health.
Machine learning is now the most popular course at Stanford — and is hailed as the key to technological transformation across many industries.
It is a type of artificial intel- ligence that enables computers to learn without being explicitly programmed, so they can grow when exposed to new data, and is used by Google, Bing, Facebook, computer vision and spam.
At PRaDA, researchers have used machine learning to develop the award-winning Toby Playpad app. Being used around the world, the app is an adaptive early intervention program for children with autism, monitoring each child’s performance and adjusting lessons accordingly.
The centre is also working with the Black Dog Institute to identify deviations in social media that could predict suicide risk and help with developing an early warning system.
“Now that we can analyse such vast amounts of data, there is enormous potential to gauge the mental health of whole populations and develop much more effective public health campaigns,” Prof Venkatesh said. To discuss suicide or depression, contact Beyond Blue on 1300 22 4636, or the Suicide Call Back Service at suicidecallbackservice.org.au