A new diagnostic tool developed by physicians and scientists from UNSW Sydney that analyses a person’s breath for signs of silicosis has the potential to catch the disease earlier rather than wait for irreversible lung damage to appear. In a study published today in the Journal of Breath Research by Professor William Alexander Donald and Conjoint Professor Deborah Yates, the researchers describe a rapid, AI-powered breath test that could transform the way silicosis is diagnosed.

The test combines mass spectrometry – a scientific technique that analyses molecules – and AI to rapidly detect silicosis from breath samples, providing a fast and non-invasive diagnostic tool for at-risk workers. xSilicosis, which is a lung disease caused by inhaling tiny crystalline particles of silicon dioxide, is a major occupational health concern in Australia, with cases now extending beyond engineered stone workers to workers in tunnelling and construction.

The Australian government has responded with a ban on engineered stone, but with new cases emerging from other high-risk industries, there is an urgent need for better diagnostic tools. Unlike traditional methods such as X-rays and CT scans that detect silicosis at later stages, the UNSW-developed test provides results in minutes. 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, lead researcher Prof. Donald from UNSW’s School of Chemistry says. This suggests that breath testing could be a practical tool for large-scale worker screening and early intervention.

Source: https://www.unsw.edu.au/newsroom/news/2025/03/ai-powered-breath-test-detects-silicosis