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Classification of diabetic retinopathy with feature selection over deep features using nature-inspired wrapper methods. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Dayana AM, Emmanuel WRS. Deep learning enabled optimized feature selection and classification for grading diabetic retinopathy severity in the fundus image. Neural Comput Appl 2022. [DOI: 10.1007/s00521-022-07471-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Hammoudi J, Bouanani NEH, Chelqi EH, Bentata Y, Nouayti H, Legssyer A, Ziyyat A. Diabetic retinopathy in the Eastern Morocco: Different stage frequencies and associated risk factors. Saudi J Biol Sci 2021; 28:775-784. [PMID: 33424367 PMCID: PMC7783821 DOI: 10.1016/j.sjbs.2020.11.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 10/28/2020] [Accepted: 11/01/2020] [Indexed: 11/22/2022] Open
Abstract
Diabetes is a major cause of morbidity and mortality worldwide. It can affect many organs and, over time, leads to serious complications. Diabetic retinopathy (DR), a specific ocular complication of diabetes, remains the leading cause of vision loss and vision impairment in adults. This work is the first in Eastern Morocco aimed at identifying the different stages of DR and to determine their frequencies and associated risk factors. It is a case-control study conducted from December 2018 to July 2019 at the ophthalmology department of Al-Irfane Clinic (Oujda). Data were obtained from a specific questionnaire involving 244 diabetic patients (122 cases with retinopathy vs 122 controls without retinopathy). All results were analyzed by the EPI-Info software. This study shows a predominance of proliferative diabetic retinopathy (PDR) with 57.4% of cases (uncomplicated proliferative diabetic retinopathy (UPDR): 23.8%; complicated proliferative diabetic retinopathy (CPDR): 33.6%). The non-proliferative diabetic retinopathy (NPDR) represents 42.6% (minimal NPDR: 8.2%; moderate NPDR: 26.2%; severe NPDR: 8.2%). The determinants of DR were insulin therapy, high blood pressure, poor glycemic control and duration of diabetes. Regarding the chronological evolution, retinopathy precedes nephropathy. Diabetic nephropathy (DN) was present in 10.6% of cases especially in patients with PDR. In summary, the frequency of PDR was higher than that of NPDR. DR appears before DN with a high frequency of DN in patients with PDR. Good glycemic control and blood pressure control, as well as early diagnosis are the major preventive measures against DR.
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Affiliation(s)
- Jamila Hammoudi
- Laboratoire de Bioressources, Biotechnologies, Ethnopharmacologie et Santé, Département de Biologie – Faculté des Sciences, Université Mohammed Premier, Oujda, Morocco
| | - Nour El Houda Bouanani
- Laboratoire de Bioressources, Biotechnologies, Ethnopharmacologie et Santé, Département de Biologie – Faculté des Sciences, Université Mohammed Premier, Oujda, Morocco
| | | | | | - Hamid Nouayti
- Laboratoire de Bioressources, Biotechnologies, Ethnopharmacologie et Santé, Département de Biologie – Faculté des Sciences, Université Mohammed Premier, Oujda, Morocco
| | - Abdelkhaleq Legssyer
- Laboratoire de Bioressources, Biotechnologies, Ethnopharmacologie et Santé, Département de Biologie – Faculté des Sciences, Université Mohammed Premier, Oujda, Morocco
| | - Abderrahim Ziyyat
- Laboratoire de Bioressources, Biotechnologies, Ethnopharmacologie et Santé, Département de Biologie – Faculté des Sciences, Université Mohammed Premier, Oujda, Morocco
- Corresponding author at: Laboratoire de Bioressources, Biotechnologies, Ethnopharmacologie et Santé, Département de Biologie – Faculté des Sciences, Université Mohammed 1er, BP 717, Boulevard Mohamed VI, 60000 Oujda, Morocco.
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Automated Microaneurysms Detection and Classification using Multilevel Thresholding and Multilayer Perceptron. J Med Biol Eng 2020. [DOI: 10.1007/s40846-020-00509-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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Robust intensity variation and inverse surface adaptive thresholding techniques for detection of optic disc and exudates in retinal fundus images. Biocybern Biomed Eng 2019. [DOI: 10.1016/j.bbe.2019.07.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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