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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Formato: Online Artículo Texto
Lenguaje:English
Publicado: IEEE 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870271/
https://www.ncbi.nlm.nih.gov/pubmed/36712318
http://dx.doi.org/10.1109/OJEMB.2022.3192780
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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.
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spelling pubmed-98702712023-01-26 Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy IEEE Open J Eng Med Biol Current Trends in Biotechnology in Human Health and Disease 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. IEEE 2022-07-20 /pmc/articles/PMC9870271/ /pubmed/36712318 http://dx.doi.org/10.1109/OJEMB.2022.3192780 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
spellingShingle Current Trends in Biotechnology in Human Health and Disease
Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy
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 Current Trends in Biotechnology in Human Health and Disease
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870271/
https://www.ncbi.nlm.nih.gov/pubmed/36712318
http://dx.doi.org/10.1109/OJEMB.2022.3192780
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