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Progress of artificial intelligence in diabetic retinopathy screening
Yue-Lin Wang1,2, Jing-Yun Yang3,4, Jing-Yuan Yang1,2
1Department of Ophthalmology, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences, Beijing, China.
Diabetes/Metabolism Research and Reviews
|October 3, 2020
Summary
Artificial intelligence (AI) aids in screening diabetic retinopathy (DR), a leading cause of blindness. AI models improve DR lesion identification, supporting early diagnosis where ophthalmologist access is limited.
Area of Science:
- Ophthalmology
- Medical Imaging
- Artificial Intelligence
Background:
- Diabetic retinopathy (DR) is a primary cause of global blindness.
- Limited access to ophthalmologists hinders timely DR diagnosis.
- Artificial intelligence (AI) shows promise in medical diagnostics.
Purpose of the Study:
- To review advancements in AI for diabetic retinopathy detection.
- To summarize automatic detection and classification models for DR diagnosis.
Main Methods:
- Literature review of AI applications in DR screening.
- Analysis of AI models for identifying DR lesions.
- Evaluation of model sensitivity and specificity.
Main Results:
- AI technology has rapidly advanced for DR screening.
- AI models demonstrate high sensitivity and specificity in identifying DR lesions.
- AI offers support for DR screening and diagnosis.
Conclusions:
- AI is a valuable tool for improving DR screening.
- AI can enhance the early identification of diabetic retinopathy.
- AI models contribute to addressing ophthalmologist shortages in DR diagnosis.
