A systematic literature review of machine learning based risk prediction models for diabetic retinopathy progression

TM Usman, YK Saheed, A Nsang, A Ajibesin… - Artificial intelligence in …, 2023 - Elsevier
Diabetic Retinopathy (DR) is the most popular debilitating impairment of diabetes and it
progresses symptom-free until a sudden loss of vision occurs. Understanding the …

[HTML][HTML] Artificial intelligence for diabetic retinopathy detection: a systematic review

A Senapati, HK Tripathy, V Sharma… - Informatics in Medicine …, 2024 - Elsevier
The incidence of diabetic retinopathy (DR) has increased at a rapid pace in recent years all
over the world. Diabetic eye illness is identified as one of the most common reasons for …

A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management

H Pan, J Sun, X Luo, H Ai, J Zeng, R Shi… - Frontiers in …, 2023 - frontiersin.org
Objective This study aimed to establish a risk prediction model for diabetic retinopathy (DR)
in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators …

Deep neural network for predicting diabetic retinopathy from risk factors

G Alfian, M Syafrudin, NL Fitriyani, M Anshari, P Stasa… - Mathematics, 2020 - mdpi.com
Extracting information from individual risk factors provides an effective way to identify
diabetes risk and associated complications, such as retinopathy, at an early stage. Deep …

Using machine learning techniques to develop risk prediction models for the risk of incident diabetic retinopathy among patients with type 2 diabetes mellitus: a cohort …

Y Zhao, X Li, S Li, M Dong, H Yu, M Zhang… - Frontiers in …, 2022 - frontiersin.org
Objective To construct and validate prediction models for the risk of diabetic retinopathy
(DR) in patients with type 2 diabetes mellitus. Methods Patients with type 2 diabetes mellitus …

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms

HY Tsao, PY Chan, ECY Su - BMC bioinformatics, 2018 - Springer
Background The risk factors of diabetic retinopathy (DR) were investigated extensively in the
past studies, but it remains unknown which risk factors were more associated with the DR …

Enhancement of diabetic retinopathy prognostication using deep learning, CLAHE, and ESRGAN

G Alwakid, W Gouda, M Humayun - Diagnostics, 2023 - mdpi.com
One of the primary causes of blindness in the diabetic population is diabetic retinopathy
(DR). Many people could have their sight saved if only DR were detected and treated in …

Deep learning algorithm predicts diabetic retinopathy progression in individual patients

F Arcadu, F Benmansour, A Maunz, J Willis… - NPJ digital …, 2019 - nature.com
The global burden of diabetic retinopathy (DR) continues to worsen and DR remains a
leading cause of vision loss worldwide. Here, we describe an algorithm to predict DR …

Predictive model and risk analysis for diabetic retinopathy using machine learning: a retrospective cohort study in China

W Li, Y Song, K Chen, J Ying, Z Zheng, S Qiao… - Bmj Open, 2021 - bmjopen.bmj.com
Objective Aiming to investigate diabetic retinopathy (DR) risk factors and predictive models
by machine learning using a large sample dataset. Design Retrospective study based on a …

[HTML][HTML] A systematic literature review of predicting diabetic retinopathy, nephropathy and neuropathy in patients with type 1 diabetes using machine learning

Q Xu, L Wang, SS Sansgiry - Journal of Medical Artificial …, 2020 - jmai.amegroups.org
Background: Diabetic retinopathy, nephropathy and neuropathy in patients with type 1
diabetes (T1D) are microvascular complications that can adversely impact disease …