Last Posted: Oct 26, 2021
- ARTEFICIAL INTELLIGENCE IN DIABETIC RETINOPATHY SCREENING. A REVIEW.
Stranák Z et al. Ceska a slovenska oftalmologie : casopis Ceske oftalmologicke spolecnosti a Slovenske oftalmologicke spolecnosti 2021 77(5) 224-231
- Combined automated screening for age-related macular degeneration and diabetic retinopathy in primary care settings.
Bhuiyan Alauddin et al. Annals of eye science 2021 6
- Effective methods of diabetic retinopathy detection based on deep convolutional neural networks.
Gu Yunchao et al. International journal of computer assisted radiology and surgery 2021
- The Importance of Close Follow-Up in Patients with Early-Grade Diabetic Retinopathy: A Taiwan Population-Based Study Grading via Deep Learning Model.
Lee Chia-Cheng et al. International journal of environmental research and public health 2021 18(18)
- Evaluation of a New Neural Network Classifier for Diabetic Retinopathy.
Katz Or et al. Journal of diabetes science and technology 2021 19322968211042665
- [Accuracy of artificial intelligence compared to trained medical technologists in diabetic retinopathy screening].
Ibáñez-Bruron María C et al. Revista medica de Chile 2021 149(4) 493-500
- Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey.
Lakshminarayanan Vasudevan et al. Journal of imaging 2021 7(9)
- Detecting diabetic retinopathy through machine learning on electronic health record data from an urban, safety net healthcare system.
Ogunyemi Omolola I et al. JAMIA open 2021 4(3) ooab066
- Performance and Limitation of Machine Learning Algorithms for Diabetic Retinopathy Screening: Meta-analysis.
Wu Jo-Hsuan et al. Journal of medical Internet research 2021 23(7) e23863
- Ethics of Artificial Intelligence in Medicine and Ophthalmology.
Abdullah Yasser Ibraheem et al. Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) 2021 10(3) 289-298
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