Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy.
Deep learning
IoT
artificial intelligence
diabetic retinopathy
eye fundus images
smart health
tensorflow
Journal
IEEE open journal of engineering in medicine and biology
ISSN: 2644-1276
Titre abrégé: IEEE Open J Eng Med Biol
Pays: United States
ID NLM: 101766631
Informations de publication
Date de publication:
2022
2022
Historique:
received:
22
05
2022
revised:
22
06
2022
accepted:
14
07
2022
entrez:
30
1
2023
pubmed:
31
1
2023
medline:
31
1
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 36712318
doi: 10.1109/OJEMB.2022.3192780
pmc: PMC9870271
doi:
Types de publication
Journal Article
Langues
eng
Pagination
124-133Références
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