4 days ago
Oman: Over 10,000 benefitted from AI-based Diabetic Retinopathy programme
Muscat – The National Diabetic Retinopathy Early Detection Programme, using artificial intelligence technologies, has successfully screened more than 10,000 eligible patients. This success reflects the rapid pace of implementation and the programme's impact in enhancing prevention of retinopathy complications and protecting diabetic patients from the risk of vision loss.
Using artificial intelligence technologies, the National Programme for Early Detection of Diabetic Retinopathy has expanded its services to include 25 healthcare facilities across the Sultanate of Oman.
This expansion is part of national efforts to improve the quality of ophthalmology services, employing modern technologies and artificial intelligence to support early diagnosis and facilitate patients' access to timely screening and treatment services.
Dr. Majid bin Salem al-Shuaibi, a consultant in retinal diseases and internal eye infections, emphasised the importance of educating diabetic patients about the importance of early screening for retinopathy through doctors and nurses in diabetes clinics. He also emphasised the importance of electronic reminders, phone calls, and the use of social media, as well as printed and visual awareness materials, to highlight the risks of delaying screening and the benefits of early detection. He noted that parallel educational campaigns are being conducted in the community to increase the demand for screening and raise awareness among patients and their families, encouraging them to undergo screening even before any symptoms appear.
The National Diabetic Retinopathy Screening Project, using artificial intelligence technologies, helps reduce the risk of vision loss and provide timely treatment. It targets all individuals diagnosed with type 1 and type 2 diabetes.
The Sultanate of Oman is the third country worldwide to implement this project, confirming its commitment to technological and digital advancements, adopting the latest technologies and employing artificial intelligence to enhance and improve diagnostic accuracy, saving time and costs, in detecting diabetic retinopathy.
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