Supergate has participated in a government-funded project for the development of a portable fundus imaging and diagnostic device combining AI and edge computing technologies.
The medical device being developed can analyze fundus images in real-time, and the images captured are immediately diagnosed by AI software through edge computing. The AI model development is being handled by Promedius, while Supergate leads the development of hardware to implement real-time analysis technology.
In South Korea, this technology allows for the early diagnosis of major retinal diseases (such as macular degeneration, glaucoma, and diabetic retinopathy), which are leading causes of blindness, as well as predicting the risk of cardiovascular diseases through a simple, low-cost, and painless test. The introduction of this technology is expected to greatly improve access to medical services in areas with inadequate medical infrastructure, and its ease of use is anticipated to increase the utilization of visitation services by local medical institutions.
Designed for patient convenience, this product not only shortens doctors’ examination times but also improves the rate of fundus examinations. As of the first half of 2018, according to the Health Insurance Review & Assessment Service data, only about 2% of diabetic patients who need regular fundus examinations actually undergo these tests. The introduction of this product is expected to contribute to the early prevention of retinal diseases and alleviate healthcare service disparities across regions and social strata.
*Fundus Examination: This is an examination of the back of the eye using an ophthalmoscope, useful in diagnosing and monitoring diseases like diabetes and arteriosclerosis, in addition to eye diseases.
*Edge computing : As a computing technology that decentralizes data processing to improve response times and system reliability, edge computing processes data close to its source, reducing latency and conserving bandwidth. This approach enhances efficiency, especially useful in IoT and real-time applications.
