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Fulltext Enhancing diabetic retinopathy classification using deep learning

Alwakid G, Gouda W, Humayun M, Jhanjhi NZ

Digit Health, 2023;9:20552076231203676.
PMID: 37766903 DOI: 10.1177/20552076231203676

Prolonged hyperglycemia can cause diabetic retinopathy (DR), which is a major contributor to blindness. Numerous incidences of DR may be avoided if it were identified and addressed promptly. Throughout recent years, many deep learning (DL)-based algorithms have been proposed to facilitate psychometric testing. Utilizing DL model that encompassed four scenarios, DR and its stages were identified in this study using retinal scans from the "Asia Pacific Tele-Ophthalmology Society (APTOS) 2019 Blindness Detection" dataset. Adopting a DL model then led to the use of augmentation strategies that produced a comprehensive dataset with consistent hyper parameters across all test cases. As a further step in the classification process, we used a Convolutional Neural Network model. Different enhancement methods have been used to raise visual quality. The proposed approach detected the DR with a highest experimental result of 97.83%, a top-2 accuracy of 99.31%, and a top-3 accuracy of 99.88% across all the 5 severity stages of the APTOS 2019 evaluation employing CLAHE and ESRGAN techniques for image enhancement. In addition, we employed APTOS 2019 to develop a set of evaluation metrics (precision, recall, and F1-score) to use in analyzing the efficacy of the suggested model. The proposed approach was also proven to be more efficient at DR location than both state-of-the-art technology and conventional DL.
Fulltext Diagnosing Melanomas in Dermoscopy Images Using Deep Learning

Alwakid G, Gouda W, Humayun M, Jhanjhi NZ

Diagnostics (Basel), 2023 May 22;13(10).
PMID: 37238299 DOI: 10.3390/diagnostics13101815

When it comes to skin tumors and cancers, melanoma ranks among the most prevalent and deadly. With the advancement of deep learning and computer vision, it is now possible to quickly and accurately determine whether or not a patient has malignancy. This is significant since a prompt identification greatly decreases the likelihood of a fatal outcome. Artificial intelligence has the potential to improve healthcare in many ways, including melanoma diagnosis. In a nutshell, this research employed an Inception-V3 and InceptionResnet-V2 strategy for melanoma recognition. The feature extraction layers that were previously frozen were fine-tuned after the newly added top layers were trained. This study used data from the HAM10000 dataset, which included an unrepresentative sample of seven different forms of skin cancer. To fix the discrepancy, we utilized data augmentation. The proposed models outperformed the results of the previous investigation with an effectiveness of 0.89 for Inception-V3 and 0.91 for InceptionResnet-V2.
Fulltext Deep learning-enhanced diabetic retinopathy image classification

Alwakid G, Gouda W, Humayun M, Jhanjhi NZ

Digit Health, 2023;9:20552076231194942.
PMID: 37588156 DOI: 10.1177/20552076231194942

OBJECTIVE: Diabetic retinopathy (DR) can sometimes be treated and prevented from causing irreversible vision loss if caught and treated properly. In this work, a deep learning (DL) model is employed to accurately identify all five stages of DR.
METHODS: The suggested methodology presents two examples, one with and one without picture augmentation. A balanced dataset meeting the same criteria in both cases is then generated using augmentative methods. The DenseNet-121-rendered model on the Asia Pacific Tele-Ophthalmology Society (APTOS) and dataset for diabetic retinopathy (DDR) datasets performed exceptionally well when compared to other methods for identifying the five stages of DR.
RESULTS: Our propose model achieved the highest test accuracy of 98.36%, top-2 accuracy of 100%, and top-3 accuracy of 100% for the APTOS dataset, and the highest test accuracy of 79.67%, top-2 accuracy of 92.%76, and top-3 accuracy of 98.94% for the DDR dataset. Additional criteria (precision, recall, and F1-score) for gauging the efficacy of the proposed model were established with the help of APTOS and DDR.
CONCLUSIONS: It was discovered that feeding a model with higher-quality photographs increased its efficiency and ability for learning, as opposed to both state-of-the-art technology and the other, non-enhanced model.
Macrophage activation syndrome triggered by systemic lupus erythematosus flare: successful treatment with a combination of dexamethasone sodium phosphate, intravenous immunoglobulin, and cyclosporine: a case report

Gouda W, Alsaqabi F, Moshrif A, Abbas AS, Abdel-Aziz TM, Islam MA

J Med Case Rep, 2021 Oct 07;15(1):497.
PMID: 34620236 DOI: 10.1186/s13256-021-03072-1

BACKGROUND: Macrophage activation syndrome is classified as a secondary form of hemophagocytic lymphohistiocytosis. It is a hyperinflammatory complication observed to be comorbid with a variety of autoimmune diseases, including adult-onset Still's disease and systemic juvenile idiopathic arthritis. Macrophage activation syndrome is less commonly detected in adult patients with systemic lupus erythematosus, which, if untreated, can be fatal, though determining the optimum treatment strategy is still a challenge.
CASE PRESENTATION: Herein, we report a case of macrophage activation syndrome in a 33-year-old Egyptian female as an unusual complication of a systemic lupus erythematosus flare in adult patients. Our patient was initially treated with a combination of intravenous methylprednisolone pulse therapy and intravenous immunoglobulin therapy, which was followed by a course of oral prednisolone and oral cyclosporine with little response. Switching from oral prednisone to intravenous dexamethasone sodium phosphate showed a more favorable clinical and biochemical response.
CONCLUSION: Macrophage activation syndrome is less commonly detected in adult patients with systemic lupus erythematosus. Our case demonstrates that dexamethasone sodium phosphate can be a successful alternative treatment for patients with systemic lupus erythematosus complicated by macrophage activation syndrome in whom the response to pulse methylprednisolone was inadequate to manage their illness, proving to be remarkably effective in a relatively short time frame.
Fulltext Ischemic stroke as the first presentation of takayasu's arteritis in young male

Gouda W, Alsaqabi F, Alkadi A, Amr HAE, Moshrif A, Mahdy ME

Clin Case Rep, 2020 Feb;8(2):258-261.
PMID: 32128168 DOI: 10.1002/ccr3.2527

Takayasu's arteritis should be kept under the differential diagnosis of stroke in all young patients. Early, proper diagnosis and treatment are necessary to reduce any further progression, morbidity, and mortality rates of the disease.
Fulltext Kikuchi-Fujimoto disease, simultaneously diagnosed with systemic lupus erythematosus in an Arabic female: an agonizing combination

Gouda W, Alsaqabi F, Almurshed M, Mostafa AA, Albasri A, Negm A, et al.

J Int Med Res, 2024 May;52(5):3000605241248884.
PMID: 38713457 DOI: 10.1177/03000605241248884

Kikuchi-Fujimoto disease (KFD), also known as histiocytic necrotizing lymphadenitis, is a rare, benign condition affecting young Oriental-Asian females. It is characterized by fever and tender cervical lymphadenopathy with an unclear aetiology, and in most longitudinal reviews, KFD occurs before systemic lupus erythematosus (SLE). Herein, the case of a 28-year-old Kuwaiti female without any relevant past medical history, who was simultaneously diagnosed with KFD and SLE following an Ebstein-Barr virus infection, is reported. The patient was treated with oral prednisolone, hydroxychloroquine, cyclosporin, and belimumab and her response was clinically and biochemically favourable. Although KFD is prevalent in Asian populations, it may affect all races. Early diagnosis of KFD is difficult, particularly when simultaneously diagnosed with SLE, but crucial to preventing inappropriate therapy. Clinicians need to know about this rare disease, especially when patients present with fever and swollen lymph nodes, due to a risk of misdiagnosis with tuberculosis or lymphoma, as these are more often thought to be the cause of such symptoms.