Speeding disease diagnosis

Speeding disease diagnosis

A particularly exciting extension of AIML’s machine learning work is the University of Adelaide’s collaborative creation of the world’s first AI microbiology screening technology for use in pathology laboratories.

Developed in partnership with Australia-based LBT Innovations (LBT), the Automated Plate Assessment System (APAS) went into production in 2017 and is attracting huge international interest.

Professor van den Hengel led the University’s six-person APAS software development team. He says the system promises to dramatically accelerate patient diagnosis and treatment, giving humanity a powerful new weapon in the fight against infectious disease.

“APAS will enable doctors to order more tests, which will give them more information, sooner. It could even allow country or developing-world hospitals to run their own tests without having to ship samples to a central lab. That would save a huge amount of time, and potentially many lives.”

The system automates the traditionally time-consuming functions performed by microbiologists in screening culture plates after incubation. It takes high-quality images of the plates, then analyses and interprets any microbial growth, matches this against key patient data, presents a diagnosis, and continually updates its own knowledge base.

Significantly, APAS also removes non-pathogenic plates from the workflow. “This is very important,” explains LBT co-founder Lusia Guthrie, now Chair of Clever Culture Systems, the joint-venture company bringing APAS to market. “In routine microbiology testing, up to 70 per cent of plates may be negative. Removing them automatically will give microbiologists more time to spend on complex decisions, enabling even greater accuracy and allowing more tests to be run.”

LBT CEO Brent Barnes believes the system will ultimately mean faster recovery for millions. “The science we’ve put into practice through APAS with the University of Adelaide could well become part of hospital protocols all over the world,” he says.

More, and more accurate, testing will see patients getting the right treatment earlier and spending less time in hospital

Guthrie believes a decision to embed a University of Adelaide researcher in its internal APAS project team was key to its success. Van den Hengel originally appointed computer scientist Rhys Hill to assist LBT in-house with proof-of-principle research. “It worked so well,” says Guthrie, “particularly in terms of communication flow, that Rhys stayed with us throughout prototype development and right up to United States Food and Drug Administration compliance.”

Keen to build on the foundation laid with APAS, the University and LBT are now jointly developing three other related medical devices utilising the University’s AI image-analysis technology.

“Our work with the University of Adelaide has taken LBT to a new level,” says Lusia. “We’ve transitioned from a ‘robotics company’ to an ‘AI company’, and now we have the opportunity to become a ‘digital health company’.”

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