Retraction Note to: Prediction of atherosclerosis pathology in retinal fundal images with machine learning approaches

Parameswari, C.; Ranjani, S. Siva

doi:10.1007/s12652-022-04286-x

Cited by 2 publications

(2 citation statements)

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“…Blockchain networks enable the development and control of transactions by users (Khezr et al 2019 ). Some existing studies are there (Padmaja and Seshadri 2021 ; Srivastava et al 2019 ; Kumar et al 2021 ; Chinnasamy and Deepalakshmi 2021 ; Parameswari and Ranjani 2022 ) which indirectly take a dig into this to enhance the area of working in healthcare.…”

Section: Taxonomy Of Application Based On the Integration Of Blockcha...mentioning

confidence: 99%

Semantic analysis of blockchain intelligence with proposed agenda for future issues

Saxena

Gayathri

2023

Int J Syst Assur Eng Manag

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Integrating blockchain technology with artificial intelligence (AI) i.e., blockchain Intelligence makes an extremely powerful tool that solves many multidimensional problems in several domains. Blockchain technology has the potential to provide links to shared data, transactions, and records in a decentralized, safe, and reliable manner, including the information and decision-making capability of AI which makes machines similar as capable as humans. This study is intended to present an updated systematic review of the integration of Blockchain and AI in various application areas. We have studied and summarized more than 100 research papers to present an updated version of the review. We also discuss the future of Blockchain technologies with AI. By integrating these two technologies results increases the security, efficiency, and productivity of the applications. Past works feature a few possible advantages of integration of Blockchain and AI, yet just give a restricted hypothetical system to depict forthcoming certifiable combination instances of the two advances. We survey and orchestrate surviving exploration on the integration of AI and Blockchain are other ways around to thoroughly build up a future research plan on the fusion of the two innovations. We also proposed an agenda to develop a secure system of cyber threat intelligence information exchange by using features of blockchain and artificial intelligence. This paper mainly focusses on explaining how collaboration of blockchain and AI gives immense boost in latest domains like Cybersecurity, Healthcare, Supply Chain Management, Finance and Banking and Social Media Analytics.

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Section: Taxonomy Of Application Based On the Integration Of Blockcha...mentioning

confidence: 99%

Semantic analysis of blockchain intelligence with proposed agenda for future issues

Saxena

Gayathri

2023

Int J Syst Assur Eng Manag

View full text Add to dashboard Cite

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“…Parameswari et al [13] aims at decreasing the disease independent variation without damaging data-based variances among the atherosclerotic eyes and images of healthy. The presented approach allows improvement of illumination in the blood vessel, via renovating them.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification

Malibari¹,

Hassine²,

Motwakel³

et al. 2022

Computers, Materials &Amp; Continua

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Atherosclerosis diagnosis is an inarticulate and complicated cognitive process. Researches on medical diagnosis necessitate maximum accuracy and performance to make optimal clinical decisions. Since the medical diagnostic outcomes need to be prompt and accurate, the recently developed artificial intelligence (AI) and deep learning (DL) models have received considerable attention among research communities. This study develops a novel Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification (MDL-BADDC) model. The proposed MDL-BADDC technique encompasses several stages of operations such as pre-processing, feature selection, classification, and parameter tuning. Besides, the proposed MDL-BADDC technique designs a novel Quasi-Oppositional Barnacles Mating Optimizer (QOBMO) based feature selection technique. Moreover, the deep stacked autoencoder (DSAE) based classification model is designed for the detection and classification of atherosclerosis disease. Furthermore, the krill herd algorithm (KHA) based parameter tuning technique is applied to properly adjust the parameter values. In order to showcase the enhanced classification performance of the MDL-BADDC technique, a wide range of simulations take place on three benchmarks biomedical datasets. The comparative result analysis reported the better performance of the MDL-BADDC technique over the compared methods.

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Retraction Note to: Prediction of atherosclerosis pathology in retinal fundal images with machine learning approaches

Cited by 2 publications

References 0 publications

Semantic analysis of blockchain intelligence with proposed agenda for future issues

Semantic analysis of blockchain intelligence with proposed agenda for future issues

Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification

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