Through their research into medical image analysis and computer-aided diagnosis, Professor Arcot Sowmya and her team are paving the way for improved disease forecasting using artificial intelligence (AI).

The process starts by equipping machines with the capacity to automatically analyse and understand medical scans and data sets. “This helps us use data-driven insights to answer disease-related questions,” says Prof. Sowmya.

For those at risk of developing various diseases, Prof. Sowmya’s research can mean earlier diagnosis, intervention and treatment – all leading to improved survival rates.

Supported by competitive industry and government funding, the research team’s findings have already been applied across the broader health area, including real-world diagnostics.

Now, the team are helping to develop biomarkers powered by AI for early detection of liver cancer.

Liver cancer is the fifth most common cancer, and, like most cancers, typically develops slowly and quietly, without causing any noticeable symptoms in its early stages.

Typically, patients with liver disease must conduct regular blood tests or undergo ultrasound imaging as part of their ongoing monitoring and treatment plans. Prof. Sowmya’s work looks at introducing additional testing methods to determine patient outcomes. These include mouth or nasal swabs, which can provide data the team needs to conduct their analysis.

“We are trying to discover if there are any easy-to-detect microorganisms or biomarkers that are potentially associated with liver cancer,” Prof. Sowmya explains. “Genetics related data is a whole new world, so we’re studying what is and isn’t related to liver cancer.”
Professor Arcot Sowmya

Patients would then repeat these tests regularly to potentially reveal an identifiable pattern.

“It all comes down to early detection – the earlier you can detect a disease, the more warning you have to offer treatment or intervention to either slow it down or provide a cure,” says Prof. Sowmya.

As this research continues to develop, Prof. Sowmya hopes to see it applied where it’s needed most.

She explains, “if we discover there is a particular set of biomarkers that help with early cancer detection, we’d like that to become part of the regular tests that patients undergo.”

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