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Oct 2, 2023 · Deep-learning models for the detection and incidence prediction of chronic ... Modelling the prevalence of diabetes mellitus risk factors based on artificial ...
Missing: Aided | Show results with:Aided
Jan 18, 2024 · This study explores an alternative approach involving retinal images, building upon the DiaNet model, the first deep learning model for diabetes detection based ...
Missing: Aided Belief
Nov 1, 2023 · GO-DBN: Gannet Optimized Deep Belief Network Based wavelet kernel ELM for Detection of Diabetic Retinopathy ... research on Diabetic Retinopathy detection (DR).
Feb 8, 2024 · This study introduces a hybrid deep learning ensemble system designed for the automated diagnosis of different stages of DR. To capture prominent features from ...
Missing: Belief | Show results with:Belief
Apr 4, 2024 · This work addresses the global problem of diabetes by exploring a revolutionary deep-learning method for early identification. Conventional convolutional neural ...
Jun 24, 2024 · The goal of the study is to automatically discover and classify the DR diagnosis by using a novel deep neural network model named MAP Concordance Regressive ...
Jul 19, 2024 · Several digital technologies have emerged to address gaps in diabetes care and DR screening, including telemedicine, artificial intelligence (AI)-assisted ...
Missing: Aided Belief
May 29, 2024 · The author of this study developed a specialized CNN structure based on the U-net model, designed explicitly for recognizing optical plates in retinal fundus ...
Missing: Belief | Show results with:Belief
Feb 28, 2024 · In this study, bidirectional gated recurrent unit (BiGRU) and Convolution neural network ... This method combines a deep belief neural network (DBNN) model for ...
Apr 16, 2024 · In this research, an intelligent recommendation-based fine-tuned EfficientNetB0 model has been proposed for quick and precise assessment for the diagnosis of ...
Missing: Belief | Show results with:Belief