Sydney researchers have made a breakthrough in the fight against silicosis, with the development of an AI-powered diagnostic tool.

The non-invasive tool, which analyses a person’s breath, can identify early signs of silicosis within minutes, which could be life-changing for at-risk workers.

Lead researcher Professor William Alexander Donald said the model works by distinguishing breath profiles of silicosis patients from healthy individuals with remarkable accuracy.

Engineered stone worker Angus Read provides a breath sample to be analysed for signs of silicosis. (.UNSW Sydney/Richard Freeman)

Silicosis is caused by inhaling fine particles of silica dust and is attributed to the introduction of artificial stone materials during the building boom of the early 2000s.

Engineered stone, a popular material often used for kitchen benches, has been linked to a surge in deadly lung disease due to its high silica content.

Australia moved to ban engineered stone last year.

Former stonemason Kyle Goodwin said early detection could have changed his life.

“If I had access to tests like this, I would have left the industry many years before I did,” he said.

CT scans of a tunneller diagnosed with silicosis. The light grey areas at the top part of the lungs represent severe scar-tissue.UNSW Sydney/Deborah Yates (UNSW Sydney/Deborah Yates)

While a ban is in place, new cases of silicosis continue to emerge from other high-risk industries.

Alexander Donald said there was an urgent need for better diagnostic tools.

“Our study shows that the AI-driven model accurately distinguished silicosis patients from healthy individuals based on their breath profiles, providing a reliable tool for early detection,” he said.

“This suggests that breath testing could be a practical tool for large-scale worker screening and early intervention.”

A new trial is currently under way at mining sites in the Hunter Valley.

Alexander Donald said researchers would like to see the tool used in the workplace over the next two years.

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