ECU researchers developed an AI algorithm that improves early detection and disease staging using medical imaging.
Key Details
- 1Supervised Contrastive Ordinal Learning algorithm was developed at Edith Cowan University.
- 2It uses imaging modalities such as bone density scans and ultrasounds for detection and staging.
- 3Achieved 85% accuracy and 79% sensitivity for Abdominal Aortic Calcification (early CVD indicator).
- 4Attained 87% accuracy/84% sensitivity in diagnosing Diabetic Retinopathy and 91% accuracy for breast cancer staging.
- 5Can differentiate between healthy and diseased individuals by learning disease-specific traits.
- 6Results will be presented at MICCAI Conference in Korea later this year.
Why It Matters

Source
EurekAlert
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