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ECU-developed AI to revolutionise early disease detection

July 28, 2025

Researchers at Edith Cowan University (ECU) have developed a cutting-edge Artificial Intelligence (AI) system that could support medical professionals in detecting and accurately diagnosing the stage of disease in a range of serious health conditions, including cardiovascular disease (CVD), diabetic eye complications, and cancer. The AI system, named the Supervised Contrastive Ordinal Learning algorithm, uses routine and non-invasive medical images such as bone density scans and ultrasounds not only for the early detection of diseases, but also to highlight disease-specific changes that help in staging and clinical interpretation.

 

ECU researcher Dr Afsah Saleem has highlighted the urgent need for non-invasive technologies to assist with the detection of medical issues such as cardiovascular disease (CVD) and diabetic retinopathy (DR). Globally, CVD affects over 640-million people and in Australia, the disease is responsible for one in every four deaths. Similarly, Diabetic Retinopathy DR, a leading cause of blindness, currently impacts more than 103 million adults worldwide, a number projected to rise to 160 million by 2045. In Australia, nearly 1.9 million people have diabetes, and about one-third develop DR over time.

These chronic diseases are often difficult to detect in the early stages because they lack obvious symptoms. Current diagnostic methods frequently rely on manual assessments of medical scans, which is a time-consuming, expensive, and subjective process, Dr Saleem said. Being a machine learning scientist and working in medical imaging, our aim is to prevent or delay permanent health losses from chronic diseases.This AI algorithm has already been successfully applied across multiple medical domains.

Source: https://www.ecu.edu.au/newsroom/articles/research/ecu-developed-ai-to-revolutionise-early-disease-detection#:~:text=Researchers%20at%20Edith%20Cowan%20University,CVD)%2C%20diabetic%20eye%20complications%2C


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