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 Selena

The Singapore Eye LEsioN Analyzer, or SELENA

(SELENA+) analyses retinal photographs using a Deep Learning System to detect 3 major eye conditions:

• diabetic eye disease, 
• glaucoma and
• age-related macular degeneration

It’s developed by the National University of Singapore School of Computing and the Singapore Eye Research Institute, and powered by IHiS.

Diabetic patients have retinal photographs taken once a year to detect signs of diabetic eye disease, a condition which can lead to blindness if not treated early. Patients undergo their usual eye scans at a clinic but instead of a human being assessing their scans, SELENA+ does the job.

In studies conducted to date, the AI-powered image reader has proven to faster and as accurate compared to human graders. Over the next two years, as SELENA+ is deployed nationwide, patients will be able to receive their results in minutes as compared to the current wait of about a day.


By the Numbers

Currently, over 100,000 patients undergo eye scans each year3

By 2050, 1 million people in Singapore estimated be diabetic

By 2050, as many as  200,000 patients may  have to be screened for  eye diseases in future

3 Under the Singapore Integrated Diabetic Retinopathy Screening programme

Benefits

PATIENTS
Earlier, more targeted treatment
Cheaper medical bill
Better quality of life
CLINICIAN
Able to reach out to patients earlier
Better decision-making supported by AI
Better manage patient conditions

Beyond SELENA+, enhancing the ability to predict cardiovascular diseases

Building on SELENA+’s capabilities, a predictive risk assessment model for cardiovascular diseases will be developed based on the analysis of retinal images.

Changes in the blood vessels in the retina can provide useful information on the individual’s cardiovascular status and risks. For example, narrowed vessels with thickened walls could be due to high blood pressure which is not well controlled. This will help identify patients with chronic conditions who are at high risk of getting a heart attack or a stroke.


AI to identify and predict your risk of cardiovascular disease

We will build on SELENA+’s capabilities to create an AI model that can be applied to retinal images.

This is a multi-prong approach which includes:

1) identifying imaging biomarkers from eye scans

2) developing predictive algorithms from existing health data

3) creating an AI engine to analyse genomic data, medical scans, clinical data and lifestyle information to create a personalised risk score for individuals

AI to create personalised treatment plans

Based on the risk score, AI will be used to support clinicians in developing a personalised care plan for at-risk patients and monitoring their progress such in the types of medication they have to take and the lifestyle changes they would need to make

AI to empower patients to better manage their chronic diseases

Through the use of a wearable device or a mobile application, AI will give patients real-time friendly nudges to comply with their care plan.

Some examples:

1) Remind them throughout the day of the lifestyle changes they need to make

2) Prompt them to adhere to medication schedules

3) Urge them to participate in the necessary screening tests

Supporting Partners