| For: | Saeed MU, Oleszczuk JD. Advances in retinal imaging modalities: Challenges and opportunities. World J Ophthalmol 2016; 6(2): 10-19 [DOI: 10.5318/wjo.v6.i2.10] |
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| URL: | https://www.wjgnet.com/2218-6239/full/v6/i2/10.htm |
| Number | Citing Articles |
| 1 |
Eman Abdelmaksoud, Shaker El-Sappagh, Sherif Barakat, Tamer Abuhmed, Mohammed Elmogy. Automatic Diabetic Retinopathy Grading System Based on Detecting Multiple Retinal Lesions. IEEE Access 2021; 9 doi: 10.1109/ACCESS.2021.3052870
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| 2 |
Qaisar Abbas, Imran Qureshi, Junhua Yan, Kashif Shaheed. Machine Learning Methods for Diagnosis of Eye-Related Diseases: A Systematic Review Study Based on Ophthalmic Imaging Modalities. Archives of Computational Methods in Engineering 2022; 29(6) doi: 10.1007/s11831-022-09720-z
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| 3 |
Ruchika Bala, Arun Sharma, Nidhi Goel. Comparative Analysis of Diabetic Retinopathy Classification Approaches Using Machine Learning and Deep Learning Techniques. Archives of Computational Methods in Engineering 2024; 31(2) doi: 10.1007/s11831-023-10002-5
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| 4 |
Anchal Lal, Neha Dave, Samia Kazi, Paul Mitchell, Aravinda Thiagalingam. Comparison of experiences and preferences following non-invasive cardiovascular risk procedures: a cross-sectional survey in participants with and without diabetes mellitus. Journal of Diabetes & Metabolic Disorders 2022; 21(1) doi: 10.1007/s40200-022-00996-3
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| 5 |
Jyoti Prakash Medhi, R. Sandeep, Pranami Datta, Tousif Khan Nizami. Intelligent identification and classification of diabetic retinopathy using fuzzy inference system. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2023; 11(6) doi: 10.1080/21681163.2023.2235014
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| 6 |
Douglas Clarkson. Information storage and transfer part 1: cyber security. Optician 2016; 2016(11) doi: 10.12968/opti.2016.11.148575
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| 7 |
Dimple Nagpal, S.N. Panda, Muthukumaran Malarvel, Priyadarshini A Pattanaik, Mohammad Zubair Khan. A review of diabetic retinopathy: Datasets, approaches, evaluation metrics and future trends. Journal of King Saud University - Computer and Information Sciences 2022; 34(9) doi: 10.1016/j.jksuci.2021.06.006
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| 8 |
J. Mary Annie Sujitha, Priya Rani, E. R. Rajkumar, P. Arulmozhivarman. ICTMI 2017. 2019; doi: 10.1007/978-981-13-1477-3_17
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| 9 |
. 2020; doi: 10.70675/c35603e9ze152z4848za4b9z87389338abee
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| 10 |
Muhammad Kamran, Shahzaib Ashraf, Muhammad Shazib Hameed. RETRACTED ARTICLE: A promising approach with confidence level aggregation operators based on single-valued neutrosophic rough sets. Soft Computing 2026; 30(S1) doi: 10.1007/s00500-023-09272-9
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| 11 |
Eman AbdelMaksoud, Sherif Barakat, Mohammed Elmogy. A computer-aided diagnosis system for detecting various diabetic retinopathy grades based on a hybrid deep learning technique. Medical & Biological Engineering & Computing 2022; 60(7) doi: 10.1007/s11517-022-02564-6
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| 12 |
Y. Aruna Suhasini Devi, K. Manjunatha Chari. ADRGS: an automatic diabetic retinopathy grading system through machine learning. Multimedia Tools and Applications 2024; 84(24) doi: 10.1007/s11042-024-20241-8
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| 13 |
Shraddha S. Shinde, Swati A. Bhavsar. Comprehensive study of ophthalmic diseases: insights, challenges and innovations. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2026; 14(1) doi: 10.1080/21681163.2024.2380091
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