Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy
Diabetic Retinopathy (DR) is one of the leading causes of blindness for people who have diabetes in the world. However, early detection of this disease can essentially decrease its effects on the patient. The recent breakthroughs in technologies, including the use of smart health systems based on Ar...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Open Journal of Engineering in Medicine and Biology |
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| Online Access: | https://ieeexplore.ieee.org/document/9834143/ |
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| author | S. Ghouali EM. Onyema MS. Guellil M A. Wajid O. Clare W. Cherifi M. Feham |
| author_facet | S. Ghouali EM. Onyema MS. Guellil M A. Wajid O. Clare W. Cherifi M. Feham |
| author_sort | S. Ghouali |
| collection | DOAJ |
| description | Diabetic Retinopathy (DR) is one of the leading causes of blindness for people who have diabetes in the world. However, early detection of this disease can essentially decrease its effects on the patient. The recent breakthroughs in technologies, including the use of smart health systems based on Artificial intelligence, IoT and Blockchain are trying to improve the early diagnosis and treatment of diabetic retinopathy. In this study, we presented an AI-based smart teleopthalmology application for diagnosis of diabetic retinopathy. The app has the ability to facilitate the analyses of eye fundus images via deep learning from the Kaggle database using Tensor Flow mathematical library. The app would be useful in promoting mHealth and timely treatment of diabetic retinopathy by clinicians. With the AI-based application presented in this paper, patients can easily get supports and physicians and researchers can also mine or predict data on diabetic retinopathy and reports generated could assist doctors to determine the level of severity of the disease among the people. |
| format | Article |
| id | doaj-art-b5cf3fae56fc46b69ca8d26c7bb21d7a |
| institution | Kabale University |
| issn | 2644-1276 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Engineering in Medicine and Biology |
| spelling | doaj-art-b5cf3fae56fc46b69ca8d26c7bb21d7a2025-08-20T03:29:31ZengIEEEIEEE Open Journal of Engineering in Medicine and Biology2644-12762022-01-01312413310.1109/OJEMB.2022.31927809834143Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics RetinopathyS. Ghouali0https://orcid.org/0000-0002-3653-873XEM. Onyema1https://orcid.org/0000-0002-4067-3256MS. Guellil2https://orcid.org/0000-0001-5768-8844M A. Wajid3https://orcid.org/0000-0003-1403-1636O. Clare4W. Cherifi5M. Feham6Faculty of Sciences and Technology, Mustapha Stambouli University, Mascara, AlgeriaDepartment of Mathematics and Computer Science, Coal City University, Enugu, NigeriaFaculty of Economics, Business and Management Sciences, MCLDL Laboratory, University of Mascara, Mascara, AlgeriaDepartment of Computer Science, Aligarh Muslim University, Aligarh, IndiaDepartment of Mathematics and Computer Science, Coal City University, Enugu, NigeriaInnoDev (Dev Software), Tlemcen, AlgeriaSTIC Lab, Faculty of Technology, University of Tlemcen, Tlemcen, AlgeriaDiabetic Retinopathy (DR) is one of the leading causes of blindness for people who have diabetes in the world. However, early detection of this disease can essentially decrease its effects on the patient. The recent breakthroughs in technologies, including the use of smart health systems based on Artificial intelligence, IoT and Blockchain are trying to improve the early diagnosis and treatment of diabetic retinopathy. In this study, we presented an AI-based smart teleopthalmology application for diagnosis of diabetic retinopathy. The app has the ability to facilitate the analyses of eye fundus images via deep learning from the Kaggle database using Tensor Flow mathematical library. The app would be useful in promoting mHealth and timely treatment of diabetic retinopathy by clinicians. With the AI-based application presented in this paper, patients can easily get supports and physicians and researchers can also mine or predict data on diabetic retinopathy and reports generated could assist doctors to determine the level of severity of the disease among the people.https://ieeexplore.ieee.org/document/9834143/Deep learningdiabetic retinopathyeye fundus imagestensorflowartificial intelligencesmart health |
| spellingShingle | S. Ghouali EM. Onyema MS. Guellil M A. Wajid O. Clare W. Cherifi M. Feham Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy IEEE Open Journal of Engineering in Medicine and Biology Deep learning diabetic retinopathy eye fundus images tensorflow artificial intelligence smart health |
| title | Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy |
| title_full | Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy |
| title_fullStr | Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy |
| title_full_unstemmed | Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy |
| title_short | Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy |
| title_sort | artificial intelligence based teleopthalmology application for diagnosis of diabetics retinopathy |
| topic | Deep learning diabetic retinopathy eye fundus images tensorflow artificial intelligence smart health |
| url | https://ieeexplore.ieee.org/document/9834143/ |
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