Opposition grasshopper optimizer based multimedia data distribution using user evaluation strategy

Sundararaj, Vinu; Selvi, M.

doi:10.1007/s11042-021-11123-4

Cited by 77 publications

(55 citation statements)

References 29 publications

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“…Thus the patient must be able to get involved in keep track of his own health and must be more involved as a key person in managing and taking decisions together with the providers of healthcare (Coulter and Collins 2011 ; Dick 1997 ). As a result, the methods and developments made to these techniques must be more viable in the case of self-management and should have a proper interface for communication (Haseena et al 2014 ; Kavitha and Ravikumar 2021 ; Rejeesh and Thejaswini 2020 , Ravikumar and Kavitha 2020 , 2021 ; Sundararaj et al 2020 ; Sundararaj 2019 ; Sundararaj and Selvi 2021 ; Vinu and Sundararaj 2016 ; Xie et al 2021 ).…”

Section: Introductionmentioning

confidence: 99%

An ensemble approach for healthcare application and diagnosis using natural language processing

Alekhya¹,

Sasikumar²

2022

Cogn Neurodyn

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Integration of healthcare records into a single application is still a challenging process There are additional issues when data becomes heterogeneous, and its application based on users does not appear to be the same. Hence, we propose an application called MEDSHARE which is a web-based application that integrates the data from various sources and helps the patient to access all their health records in a single point of source. Apart just from the collection of data, this portal enables the process of diagnosis using Natural language processing. The process is carried out by fuzzy logic ruleset which is generated by using NLP packages. The resulted information is given to the SVM classifier which helps in the prediction of diseases resulting in 89% of accuracy and standing the best compared to other classifiers. Finally, the observations resulted are sent to the front end application and the concerned user mobile through text message in their own native language for which translation package is been used.

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Section: Introductionmentioning

confidence: 99%

An ensemble approach for healthcare application and diagnosis using natural language processing

Alekhya¹,

Sasikumar²

2022

Cogn Neurodyn

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“…To achieve this purpose, a new generation of processes must be developed. These methods must be capable of dealing with high-resolution images while being computationally simple [ 11 – 13 ].…”

Section: Introductionmentioning

confidence: 99%

Multithreshold Image Segmentation Technique Using Remora Optimization Algorithm for Diabetic Retinopathy Detection from Fundus Images

Vinayaki

Kalaiselvi

2022

Neural Process Lett

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One of the most common complications of diabetes mellitus is diabetic retinopathy (DR), which produces lesions on the retina. A novel framework for DR detection and classification was proposed in this study. The proposed work includes four stages: pre-processing, segmentation, feature extraction, and classification. Initially, the image pre-processing is performed and after that, the Multi threshold-based Remora Optimization (MTRO) algorithm performs the vessel segmentation. The feature extraction and classification process are done by using a Region-based Convolution Neural Network (R-CNN) with Wild Geese Algorithm (WGA). Finally, the proposed R-CNN with WGA effectively classifies the different stages of DR including Non-DR, Proliferative DR, Severe, Moderate DR, Mild DR. The experimental images were collected from the DRIVE database, and the proposed framework exhibited superior DR detection performance. Compared to other existing methods like fully convolutional deep neural network (FCDNN), genetic-search feature selection (GSFS), Convolutional Neural Networks (CNN), and deep learning (DL) techniques, the proposed R-CNN with WGA provided 95.42% accuracy, 93.10% specificity, 93.20% sensitivity, and 98.28% F-score results.

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“…10 In recent years, machine learning [11][12][13][14] and optimization methods [15][16][17][18][19][20][21][22][23] has been achieved better results in engineering applications. [24][25][26][27][28][29] Over the past few years, detecting fake review has been attracted a great deal of attention from research and business communities. For reviews in reflecting legitimate and genuine user opinions and experiences, fake review detection is considered as a crucial issue.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy artificial bee colony‐based CNN‐LSTM and semantic feature for fake product review classification

Jacob¹,

Rajendran²

2021

Concurrency and Computation

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In recent years, online reviews are considered as the most significant resource for consumers to make a decision regarding the purchase of a particular product. The reviews can either encourage or relegate a product; therefore posting fake reviews has turned into a money-spinning business in the modern period. The detection of fake reviews has become a center of attraction for various business people. This research study aims in detecting fake product reviews using four significant phases namely the data pre-processing, feature extraction, feature selection, and classification. The features obtained in the pre-processing phase are extracted and selected using chi-squared technique to obtain a delegate subset among all data and to reduce the complication issues. Then a CNNLSTM-FABC approach classifies and detects the review as fake or real. Finally, the performance evaluation and the comparative analysis are carried out to determine the effectiveness of the proposed approach. The results reveal that the proposed approach performs well irrespective of the product type and sentiment polarity.

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Opposition grasshopper optimizer based multimedia data distribution using user evaluation strategy

Cited by 77 publications

References 29 publications

An ensemble approach for healthcare application and diagnosis using natural language processing

An ensemble approach for healthcare application and diagnosis using natural language processing

Multithreshold Image Segmentation Technique Using Remora Optimization Algorithm for Diabetic Retinopathy Detection from Fundus Images

Fuzzy artificial bee colony‐based CNN‐LSTM and semantic feature for fake product review classification

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