Ghouali S, Onyema E M, Guellil M S, Wajid M A, Clare O, Cherifi W, Feham M
Faculty of Sciences and TechnologyMustapha Stambouli University Mascara 29000 Algeria.
Department of Mathematics and Computer ScienceCoal City University Enugu 400104 Nigeria.
IEEE Open J Eng Med Biol. 2022 Jul 20;3:124-133. doi: 10.1109/OJEMB.2022.3192780. eCollection 2022.
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.
糖尿病视网膜病变(DR)是全球糖尿病患者失明的主要原因之一。然而,早期发现这种疾病基本上可以降低其对患者的影响。包括基于人工智能、物联网和区块链的智能健康系统在内的技术最近取得的突破,正试图改善糖尿病视网膜病变的早期诊断和治疗。在本研究中,我们提出了一种基于人工智能的智能远程眼科应用程序,用于诊断糖尿病视网膜病变。该应用程序能够通过使用Tensor Flow数学库从Kaggle数据库进行深度学习,促进眼底图像分析。该应用程序将有助于推动移动健康(mHealth)发展,并使临床医生能够及时治疗糖尿病视网膜病变。借助本文提出的基于人工智能的应用程序,患者可以轻松获得支持,医生和研究人员也可以挖掘或预测糖尿病视网膜病变的数据,生成的报告可以帮助医生确定人群中该疾病的严重程度。