A critical review: Psychophysical assessments of diabetic retinopathy

Chen, Xing D.; Gardner, Thomas W.

doi:10.1016/j.survophthal.2020.08.003

Cited by 27 publications

(22 citation statements)

References 139 publications

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“…We expect that by creating and applying these calculations to actual patients, we can recognise basic maladies. At that point, this early location will prompt timely treatment that can anticipate visual deficiency [18].…”

Section: Figure 1: Development Of Eye Disease Produced By Diabetesmentioning

confidence: 99%

A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification

Zia¹,

Irum²,

Qadri³

et al. 2022

Computers, Materials &Amp; Continua

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Diabetes or Diabetes Mellitus (DM) is the upset that happens due to high glucose level within the body. With the passage of time, this polygenic disease creates eye deficiency referred to as Diabetic Retinopathy (DR) which can cause a major loss of vision. The symptoms typically originate within the retinal space square in the form of enlarged veins, liquid dribble, exudates, haemorrhages and small scale aneurysms. In current therapeutic science, pictures are the key device for an exact finding of patients' illness. Meanwhile, an assessment of new medicinal symbolisms stays complex. Recently, Computer Vision (CV) with deep neural networks can train models with high accuracy. The thought behind this paper is to propose a computerized learning model to distinguish the key precursors of Dimensionality Reduction (DR). The proposed deep learning framework utilizes the strength of selected models (VGG and Inception V3) by fusing the extracated features. To select the most discriminant features from a pool of features, an entropy concept is employed before the classification step. The deep learning models are fit for measuring the highlights as veins, liquid dribble, exudates, haemorrhages and miniaturized scale aneurysms into various classes. The model will ascertain the loads, which give the seriousness level of the patient's eye. The model will be useful to distinguish the correct class of seriousness of diabetic retinopathy pictures.

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Section: Figure 1: Development Of Eye Disease Produced By Diabetesmentioning

confidence: 99%

A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification

Zia¹,

Irum²,

Qadri³

et al. 2022

Computers, Materials &Amp; Continua

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“…Microvascular consequences of diabetes mellitus (DM), such as diabetic retinopathy (DR), are prevalent and severe. 1 DR severity increases the risk of vision loss and other ocular proliferative disorders, such as macular degeneration. 2 …”

Section: Introductionmentioning

confidence: 99%

Diabetic Retinopathy as a Predictor of Angiographic Coronary Atherosclerosis Severity in Patients with Type 2 Diabetes Mellitus

Eid¹,

Mounir²,

Etriby³

et al. 2022

DMSO

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Background Diabetic retinopathy (DR) is one of the most prevalent consequences of diabetes mellitus (DM). Much emphasis has been focused on the link between DR and cardiovascular disorders in patients with type 2 diabetes (T2DM). However, there is little information about the relation between the degree of DR and coronary atherosclerosis severity in Egyptian patients. Aim To assess the correlation between the degree of DR and the coronary atherosclerosis severity in T2DM. Patients and Methods This work included 140 diabetic patients with T2DM who underwent diagnostic coronary angiography because of suspected coronary artery disease (CAD). All participants were evaluated by history, fundus assessment, laboratory tests (lipid profile and glycated hemoglobin [HbA1c]), and selective coronary angiography. The severity of coronary artery lesion was detected by Gensini score and vessel score. Results Patients with DR had a significantly higher Gensini score (67.86± 44.56 versus 5.93± 9.02, P < 0.001) and a vessel score (2.29± 0.86 versus 0.50± 0.66, P < 0.001). There was a significant relation between the degree of DR, Gensini score (P < 0.001), and vessel score (P < 0.001), as both scores increased according to the severity of DR. The presence and degree of retinopathy were the only independent factors linked to the severity score in multivariate linear regression analyses (P < 0.001). Conclusion The presence and degree of DR are independent predictors of severe coronary atherosclerosis. Therefore, when evaluating whether a patient with T2DM is at high risk for CAD, the DR degree should be taken into consideration.

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“…There are 2.6 million people had been suffered from visual impairment due to DR until 2015 ( 4 ), and this number has been growing over time. In China, 40% of diabetic patients suffer from DR ( 5 ), and 1/10 of DR will develop into vision-threatening DR ( 6 ). So, DR is considered to be an important factor leading to visual impairment and even blindness in working-age diabetic patients.…”

Section: Introductionmentioning

confidence: 99%

The Association of Homocysteine and Diabetic Retinopathy in Homocysteine Cycle in Chinese Patients With Type 2 Diabetes

Luo

Zhang²,

Zhang³

et al. 2022

Front. Endocrinol.

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ObjectiveThis study aimed to explore the relationship between homocysteine (Hcy) and diabetic retinopathy (DR) and the impacts of the Hcy pathway on this relationship against this background.MethodsThis study retrieved 1979 patients with type 2 diabetes (T2D) from the First Affiliated Hospital of Liaoning Medical University in Jinzhou, Liaoning Province, China. Multiple logistic regression was used to analyze the effects of Hcy cycle on the relationship between Hcy and DR. Spearman’s rank correlation analysis was used to analyze the correlation between risk factors related to DR progression and Hcy. Finally, the results of logistic regression were supplemented by mediation analysis.ResultsWe found there was a negative correlation between low concentration of Hcy and DR (OR : 0.83, 95%CI: 0.69-1). After stratifying all patients by cysteine (Cys) or Methionine (Met), this relationship remained significant only in low concentration of Cys (OR: 0.75, 95%CI: 0.61-0.94). Through the RCS curve, we found that the effect of Hcy on DR presents a U-shaped curve relationship. Mediating effect in Met and Hcy cycles was also significant [Total effect c (OR: 0.968, 95%CI: 0.938-0.998), Direct effect path c’ (OR: 0.969, 95%CI: 0.940-0.999), Path a (OR: 1.047, 95%CI: 1.004-1.091), Path b (OR: 0.964, 95%CI: 0.932-0.998)].ConclusionsThe relationship between Hcy and DR presents a U-shaped curve and the homocysteine cycle pathway has an impact on it. And too low concentration of Hcy indicates a lack of other substances, such as vitamins. It is suggested that the progression of DR is the result of a combination of many risk factors. Further prospective studies are needed to determine the role of Hcy in the pathogenesis of DR.

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A critical review: Psychophysical assessments of diabetic retinopathy

Cited by 27 publications

References 139 publications

A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification

A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification

Diabetic Retinopathy as a Predictor of Angiographic Coronary Atherosclerosis Severity in Patients with Type 2 Diabetes Mellitus

The Association of Homocysteine and Diabetic Retinopathy in Homocysteine Cycle in Chinese Patients With Type 2 Diabetes

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