Dr.Noon CVD

Retinal Coronary Artery Calcification Score A.I

The only A.I that goes head to head with CT Scan and CAC Score. It's impressive correlation with CT scans means CACS test will be affordable and accessible.

How Does Dr.Noon CVD Work?

Dr. Noon CVD’s artificial intelligence is trained using deep learning on racially diverse data comprising more than 2.8 million images and has been compared against CAC scores from CT scans. It classifies cardiovascular event risk into three categories, achieving an AUC of 0.74 and a C-index score of 0.81.

Key Benefits

High Accuracy

Delivers reliable cardiovascular risk predictions with performance comparable to cardiac CT imaging.

Safe & Non-Invasive

No needles or radiation are required, ensuring a safe and comfortable experience for patients.

Cost-Effective

Provides a more affordable alternative to traditional cardiovascular screening methods.

Providing the best features

Detects coronary artery score via retinal images.

Significant increased predictive accuracy of CVD events compared to Framingham Heart SOCRE.

High level comparison study between CAC Score via retina and CT Scan. Achieved AUC performance of 0.74

Sample Report

Dr.Noon CVD is clinically validated

Achieves an AUC of 0.74 when compared with CT scan CACS for risk-ranking capability. Dr.Noon CVD is also tested to achieve a C-index of 0.81 for cardiovascular risk prediction over time, outperforming the Framingham Heart SCORE.

Large-scale dataset

Extensive dataset representing diverse populations, including Asian populations (Singapore), Caucasian, Latino, and African populations (UK Biobank), as well as the Korean population (Korea). Updated AUC and C-index performance, based on 2.8 million retinal images, will be published soon.