Deep Neural Network for Predicting Diabetic Retinopathy from Risk Factors

Mathematics

Pavel Stasa¹  Jiri Svub¹  Muhammad Syafrudin²  Jongtae Rhee²  NormaLatif Fitriyani²  Ganjar Alfian³  Muhammad Anshari⁴ 

[1] Department of Economics and Control Systems, Faculty of Mining and Geology, VSB–Technical University of Ostrava, 70800 Ostrava-Poruba, Czech Republic;Department of Industrial and Systems Engineering, Dongguk University, Seoul 04620, Korea;Industrial Artificial Intelligence (AI) Research Center, Nano Information Technology Academy, Dongguk University, Seoul 04626, Korea;School of Business & Economics, University Brunei Darussalam, Gadong BE1410, Brunei;

关键词: retinopathy;    risk factor;    machine learning;    deep neural network;    recursive feature elimination;    deep learning;   

DOI  :  10.3390/math8091620

来源: DOAJ

【 摘 要 】

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 learning and machine learning algorithms are being utilized to extract information from individual risk factors to improve early-stage diagnosis. This study proposes a deep neural network (DNN) combined with recursive feature elimination (RFE) to provide early prediction of diabetic retinopathy (DR) based on individual risk factors. The proposed model uses RFE to remove irrelevant features and DNN to classify the diseases. A publicly available dataset was utilized to predict DR during initial stages, for the proposed and several current best-practice models. The proposed model achieved 82.033% prediction accuracy, which was a significantly better performance than the current models. Thus, important risk factors for retinopathy can be successfully extracted using RFE. In addition, to evaluate the proposed prediction model robustness and generalization, we compared it with other machine learning models and datasets (nephropathy and hypertension–diabetes). The proposed prediction model will help improve early-stage retinopathy diagnosis based on individual risk factors.

【 授权许可】

Unknown