An Artificial Intelligence (AI) deep learning system (DLS) that reduces the diagnosis process for eye diseases from an average of 30 minutes to just 8½ minutes won the gold award under the Most Promising Innovation category at the fourth annual Techblazer Awards. The Techblazer Awards are Singapore’s highest accolade for tech innovation.
The Singapore Eye LEson Analyzer+ (SELENA+), was developed by Singapore Eye Research Institute and the National University of Singapore School of Computing in partnership with a local healthtech company. Diabetic retinopathy (DR) poses a large economic burden on the healthcare system with nearly 1 in 10 diabetes patients developing vision-threatening DR Early detection, accurate evaluation and timely treatments are effective in preventing blindness. However, the ability to implement this is limited by the manual nature of examining a patient’s retinal images.
This is especially a problem in Asia due to the rising incidence of diabetes, the absence of a CAD tool for automated detection of DR and the lack of centres specializing in fundus image grading. There is a great need for an automated DR detection tool.
SELENA employs the latest image analysis and state-of-the-art machine learning techniques to serve as an automated, real-time detection tool that can match human grading. It has undergone extensive validation testing to screen DR by automatically classifying the diabetic patients into those who need a medical referral, and do not need further assessment or treatment.
The traditional diagnosis process, which involves sending the fundus images to a human grader, takes about a day to yield results. Based on the technology, people can send the image online and onto the cloud service, and they actually return the results to the patient within 15 to 20 seconds
Selena+ has been implemented at all polyclinics here as part of a programme to conduct eye screenings for diabetic patients. In the private sector, 20 optometry stores and several general practitioner clinics under the Primary Care Network have also implemented the AI-powered DLS.
Globally, SELENA+ has been deployed in 22 countries, and EyRIS is looking to expand into other markets including China and the United States. By the end of the year, the company also hopes to develop new verticals that can detect other conditions, such as chronic kidney disease, stroke and cardiovascular diseases, using the same fundus images.
Another winner at the Techblazer Awards was a team from the National University of Singapore and Singapore University of Technology and Design, who received a gold award under the Student Techblazer category for Skilio, an AI-powered digital soft skills portfolio.
The AI uses natural language processing to identify skillsets of users – from students in secondary schools to post-graduates – based on the co-curricular activity (CCA), competition and internship experiences that they upload onto the platform.
As reported by OpenGov Asia, AI Singapore (AISG) is looking to boost Singapore’s Artificial Intelligence (AI) and machine learning (ML) capabilities with the use of graph technology, which enhances analytics by finding unknown relationships in data that are not being identified by traditional means. A graph database, with its structure of nodes and edges, creates connecting and traversing links which allow for accelerated processing of inter-connected data. This makes it possible to process terabytes of data and traverse millions of connections in a fraction of a second.
According to Asia Pacific AI Readiness Index, Singapore is again at the top spot for readiness in the adoption of AI, compared to 10 other economies in the region. the index assesses the readiness of governments, businesses, and consumers across eleven APAC economies in their adoption of AI technologies.
