Back to all news
UK Researchers Launch Unbiased AI Testing Platform for Diabetic Retinopathy Screening
Researchers unveiled a new independent platform for fair, large-scale evaluation of commercial AI algorithms detecting diabetic eye disease within the NHS.
Key Details
- 1First real-world head-to-head platform to evaluate commercial AI algorithms for NHS use in detecting diabetic eye disease.
- 2Eight CE marked AI algorithms tested on 1.2 million retinal images from one of the UK’s largest and most diverse screening programs.
- 3Algorithm performance (accuracy) ranged from 83.7% to 98.7% for clinically relevant diabetic eye disease, outperforming or matching human graders.
- 4Algorithms’ accuracy remained consistent across varied ethnic groups; first such assessment at this scale.
- 5AI analyzed images in 240ms–45s compared to up to 20 minutes for humans, vastly improving efficiency.
- 6Funded by NHS Transformation Directorate, The Health Foundation, and Wellcome Trust; study published in The Lancet Digital Health.
Why It Matters
This platform addresses critical gaps in algorithmic fairness, transparency, and efficiency for imaging AI, setting a rigorous new standard for evaluation and deployment in national health systems. Its scalable, unbiased testing approach could serve as a blueprint for clinical AI adoption across radiology and other disease areas.
Source
EurekAlert
Related News
•EurekAlert
AI Predicts Risks for Outpatient Stem Cell Therapy in Myeloma
Researchers use machine learning to predict adverse events during stem cell therapy for multiple myeloma, improving outpatient safety.
•EurekAlert
AI-Enhanced CT Heart Fat Measurement Boosts Cardiovascular Risk Prediction
AI-derived measurement of heart fat from CT scans significantly improves long-term cardiovascular disease risk prediction.
•EurekAlert
Molecular Test BiliSeq Greatly Improves Bile Duct Cancer Detection
The BiliSeq molecular test developed at UPMC doubled detection sensitivity for bile duct cancer compared to standard pathology.