Cardiovascular Diseases: A New Early Warning System and Scarcity – Horus ML

Horus ML has developed a low-cost cardiovascular screening system, which uses AI to rapidly analyse retinal images in primary care settings.

Approximately 50% of heart attacks occur in individuals previously classified as low risk. Preventative healthcare is held back by a lack of effective cardiovascular screening in primary care centres, which don’t have the necessary specialised equipment and trained personnel, according to Horus ML, a Madrid-based startup.

Horus has developed a new cardiovascular screening system, called AItheroscope, which combines advanced deep learning algorithms with RetinoLens, a low-cost optical device, to analyse retinal images and detect subclinical atherosclerosis – asymptomatic plaque buildup in the arteries. Designed to generate a diagnosis in less than 10 seconds, AItheroscope could be used by primary care clinicians and even individuals in their homes.

As well as lowering diagnostic costs, the system promises to prevent progression to severe cardiovascular events, and reduce hospitalisations. Horus believes AItheroscope will also address gender bias in cardiovascular diagnosis through automated, unbiased screening. To accelerate development, the start-up has secured more than over €750,000 in public funding.

Now performing clinical validation of the new system with Madrid’s Hospital Infanta Leonor, Horus is aiming to have AItheroscope in use by 20 primary care centres and three hospitals in Spain by the end of 2025. Following a successful Spanish deployment, it is planning to sell the system internationally, targeting countries with similar healthcare systems.

Horus estimates that AItheroscope can address a global market of one billion people who currently have no access to effective cardiovascular screening, as they live in underserved rural and resource-limited areas where specialised cardiovascular care is unavailable.