Diabetic Retinopathy Detection based on Hybrid Feature Extraction and SVM

Nazir, Tahira; Javed, Ali; Masood, Momina; Rashid, Junaid; Kanwal, Samira

doi:10.1109/macs48846.2019.9024812

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…In online purchase consumers interact in a virtual environment through the website interface. In our daily lives the internet is emerged as a new method of communication and information exchanging.Therefore the acceptability of this medium is cause of increase in number of internet users which clearly indicates the increase in online shopping [18]. Trust is psychological state and it is defined as the desire of one party to depend on the behavior of others, especially when these behaviors have implications for the first party [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of customer’s Psychological factors leading to purchase on online shopping: A study from the perspective of e-commerce in underdeveloped countries

2018

ARJBM

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Shopping with the comfort of own couch on internet is named as online shopping. Earlier, the customers of Pakistan were not open-minded but now they adopted online shopping and e-commerce website are getting popularity. The purpose of this paper is to examine the effect of customer's psychological factors leading to purchase on online shopping. A model was made to examine the factors online shopping and it was tested empirically using a sample of 393. The questionnaire strategy was used for this research. Descriptive statistics and regression was run to find the results. The paper found Attitude, Risk and Trust to be the most effective components of the psychological construct of the research model, making them key influencer of online shopping in under developed countries. The scope of this study is limited to Faisalabad. The paper outlines ways to effectively work on psychological factors for increasing online shoppers of under developed countries towards e-commerce websites. A marketing manager or website developer can follow these outlines in order to make policy for online shoppers of under developed countries.

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Section: Literature Reviewmentioning

confidence: 99%

Effect of customer’s Psychological factors leading to purchase on online shopping: A study from the perspective of e-commerce in underdeveloped countries

2018

ARJBM

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“…This condition, characterized by damage to the retinal blood vessels, highlights the importance of early and accurate detection [1] , [2] , [3] . In this context, eye fundus image analysis plays a critical role, considering its ability to identify early signs of diabetic retinopathy [4] , [5] .…”

Section: Introductionmentioning

confidence: 99%

“…While these emerging trends open new avenues for more efficient diagnosis, challenges remain, particularly in understanding and integrating findings from scattered studies. [4] , [12] , [13] .…”

Section: Introductionmentioning

confidence: 99%

Fundus Image Feature Extraction in Diabetic Retinopathy: A Bibliometric Analysis Approach

Costaner,

Harun

2024

Proceedings of the 2nd International Conference on Environmental, Energy, and Earth Science, ICEEES 2023, 30 October 2023, Peka

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Diabetic retinopathy is the main cause of vision loss in diabetes patients. Eye fundus image analysis plays a critical role in identifying early signs of diabetic retinopathy. Rapid developments in the fields of digital image processing and artificial intelligence have brought about a revolution in fundus image feature extraction methods, enabling the identification of small details such as changes in blood vessels, the presence of microaneurysms, and exudates, all of which are important indicators of the progression of diabetic retinopathy. In this study, we used an analytical approach from Scopus and used bibliometrics with the Vosviewer application to map and assess research developments in fundus image feature extraction in the context of diabetic retinopathy. The results of the analysis of fundus image research on diabetic retinopathy show an increase in the number of publications every year, with India as the country with the most publications. Feature extraction techniques remain the focus of research, with several feature selection methods that can be used to detect diabetic retinopathy. In addition, the subject area of computer science is experiencing an increase in fundus image research of diabetic retinopathy, indicating the contribution of technology and related methods in the research of this disease.

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“…DL-based artificial intelligence has recently advanced in numerous medical sectors and has proven to be the most successful artificial-intelligence-based analysis in computer-aided imaging [10]. Many different fields have used artificial intelligence for image classification and image detection, including the diagnosis of gastrointestinal neoplasms [11], the comparison of drugs [12], the diagnosis of retinal disease [13,14], and the detection of metaphase [15].…”

Section: Introductionmentioning

confidence: 99%

A Circular Box-Based Deep Learning Model for the Identification of Signet Ring Cells from Histopathological Images

Albahli,

Nazir

2023

Bioengineering

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Signet ring cell (SRC) carcinoma is a particularly serious type of cancer that is a leading cause of death all over the world. SRC carcinoma has a more deceptive onset than other carcinomas and is mostly encountered in its later stages. Thus, the recognition of SRCs at their initial stages is a challenge because of different variants and sizes and illumination changes. The recognition process of SRCs at their early stages is costly because of the requirement for medical experts. A timely diagnosis is important because the level of the disease determines the severity, cure, and survival rate of victims. To tackle the current challenges, a deep learning (DL)-based methodology is proposed in this paper, i.e., custom CircleNet with ResNet-34 for SRC recognition and classification. We chose this method because of the circular shapes of SRCs and achieved better performance due to the CircleNet method. We utilized a challenging dataset for experimentation and performed augmentation to increase the dataset samples. The experiments were conducted using 35,000 images and attained 96.40% accuracy. We performed a comparative analysis and confirmed that our method outperforms the other methods.

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Diabetic Retinopathy Detection based on Hybrid Feature Extraction and SVM

Cited by 5 publications

References 16 publications

Effect of customer’s Psychological factors leading to purchase on online shopping: A study from the perspective of e-commerce in underdeveloped countries

Effect of customer’s Psychological factors leading to purchase on online shopping: A study from the perspective of e-commerce in underdeveloped countries

Fundus Image Feature Extraction in Diabetic Retinopathy: A Bibliometric Analysis Approach

A Circular Box-Based Deep Learning Model for the Identification of Signet Ring Cells from Histopathological Images

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