FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4206961924> ?p ?o ?g. }

• W4206961924 abstract "At these times, internet of things (IoT) technologies have become ubiquitous in the healthcare sector. Because of the increasing needs of IoT, massive quantity of patient data is being gathered and is utilized for diagnostic purposes. The recent developments of artificial intelligence (AI) and deep learning (DL) models are commonly employed to accurately identify the diseases in real-time scenarios. Despite the benefits, security, energy constraining, insufficient training data are the major issues which need to be resolved in the IoT enabled medical field. To accomplish the security, blockchain technology is recently developed which is a decentralized architecture that is widely utilized. With this motivation, this paper introduces a new blockchain with DL enabled secure medical data transmission and diagnosis (BDL-SMDTD) model. The goal of the BDL-SMDTD model is to securely transmit the medical images and diagnose the disease with maximum detection rate. The BDL-SMDTD model incorporates different stages of operations such as image acquisition, encryption, blockchain, and diagnostic process. Primarily, moth flame optimization (MFO) with elliptic curve cryptography (ECC), called MFO-ECC technique is used for the image encryption process where the optimal keys of ECC are generated using MFO algorithm. Besides, blockchain technology is utilized to store the encrypted images. Then, the diagnostic process involves histogram-based segmentation, Inception with ResNet-v2-based feature extraction, and support vector machine (SVM)-based classification. The experimental performance of the presented BDL-SMDTD technique has been validated using benchmark medical images and the resultant values highlighted the improved performance of the BDL-SMDTD technique. The proposed BDL-SMDTD model accomplished maximum classification performance with sensitivity of 96.94%, specificity of 98.36%, and accuracy of 95.29%, whereas the feature extraction is performed based on ResNet-v2" @default.
• W4206961924 created "2022-01-26" @default.
• W4206961924 creator A5015555101 @default.
• W4206961924 creator A5022520259 @default.
• W4206961924 creator A5033711346 @default.
• W4206961924 creator A5044771843 @default.
• W4206961924 creator A5052530116 @default.
• W4206961924 creator A5091180044 @default.
• W4206961924 date "2022-01-20" @default.
• W4206961924 modified "2023-10-16" @default.
• W4206961924 title "Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model" @default.
• W4206961924 cites W2509553213 @default.
• W4206961924 cites W2605362632 @default.
• W4206961924 cites W2771747728 @default.
• W4206961924 cites W2774398736 @default.
• W4206961924 cites W2908737503 @default.
• W4206961924 cites W2914212774 @default.
• W4206961924 cites W2922361312 @default.
• W4206961924 cites W2945012341 @default.
• W4206961924 cites W2951478627 @default.
• W4206961924 cites W2971863623 @default.
• W4206961924 cites W2974262067 @default.
• W4206961924 cites W2982300697 @default.
• W4206961924 cites W2997497674 @default.
• W4206961924 cites W3033466636 @default.
• W4206961924 cites W3036031408 @default.
• W4206961924 cites W3044194019 @default.
• W4206961924 cites W3045449233 @default.
• W4206961924 cites W3045658393 @default.
• W4206961924 cites W3046301713 @default.
• W4206961924 cites W3110102192 @default.
• W4206961924 cites W3129975510 @default.
• W4206961924 cites W3143466921 @default.
• W4206961924 doi "https://doi.org/10.1142/s1793962322410069" @default.
• W4206961924 hasPublicationYear "2022" @default.
• W4206961924 type Work @default.
• W4206961924 citedByCount "33" @default.
• W4206961924 countsByYear W42069619242022 @default.
• W4206961924 countsByYear W42069619242023 @default.
• W4206961924 crossrefType "journal-article" @default.
• W4206961924 hasAuthorship W4206961924A5015555101 @default.
• W4206961924 hasAuthorship W4206961924A5022520259 @default.
• W4206961924 hasAuthorship W4206961924A5033711346 @default.
• W4206961924 hasAuthorship W4206961924A5044771843 @default.
• W4206961924 hasAuthorship W4206961924A5052530116 @default.
• W4206961924 hasAuthorship W4206961924A5091180044 @default.
• W4206961924 hasConcept C108583219 @default.
• W4206961924 hasConcept C111919701 @default.
• W4206961924 hasConcept C115961682 @default.
• W4206961924 hasConcept C119857082 @default.
• W4206961924 hasConcept C12267149 @default.
• W4206961924 hasConcept C124101348 @default.
• W4206961924 hasConcept C13280743 @default.
• W4206961924 hasConcept C148730421 @default.
• W4206961924 hasConcept C154945302 @default.
• W4206961924 hasConcept C185798385 @default.
• W4206961924 hasConcept C202444582 @default.
• W4206961924 hasConcept C205649164 @default.
• W4206961924 hasConcept C2779687700 @default.
• W4206961924 hasConcept C33923547 @default.
• W4206961924 hasConcept C38652104 @default.
• W4206961924 hasConcept C41008148 @default.
• W4206961924 hasConcept C53533937 @default.
• W4206961924 hasConcept C9652623 @default.
• W4206961924 hasConcept C98045186 @default.
• W4206961924 hasConceptScore W4206961924C108583219 @default.
• W4206961924 hasConceptScore W4206961924C111919701 @default.
• W4206961924 hasConceptScore W4206961924C115961682 @default.
• W4206961924 hasConceptScore W4206961924C119857082 @default.
• W4206961924 hasConceptScore W4206961924C12267149 @default.
• W4206961924 hasConceptScore W4206961924C124101348 @default.
• W4206961924 hasConceptScore W4206961924C13280743 @default.
• W4206961924 hasConceptScore W4206961924C148730421 @default.
• W4206961924 hasConceptScore W4206961924C154945302 @default.
• W4206961924 hasConceptScore W4206961924C185798385 @default.
• W4206961924 hasConceptScore W4206961924C202444582 @default.
• W4206961924 hasConceptScore W4206961924C205649164 @default.
• W4206961924 hasConceptScore W4206961924C2779687700 @default.
• W4206961924 hasConceptScore W4206961924C33923547 @default.
• W4206961924 hasConceptScore W4206961924C38652104 @default.
• W4206961924 hasConceptScore W4206961924C41008148 @default.
• W4206961924 hasConceptScore W4206961924C53533937 @default.
• W4206961924 hasConceptScore W4206961924C9652623 @default.
• W4206961924 hasConceptScore W4206961924C98045186 @default.
• W4206961924 hasIssue "04" @default.
• W4206961924 hasLocation W42069619241 @default.
• W4206961924 hasOpenAccess W4206961924 @default.
• W4206961924 hasPrimaryLocation W42069619241 @default.
• W4206961924 hasRelatedWork W2989851257 @default.
• W4206961924 hasRelatedWork W3209862047 @default.
• W4206961924 hasRelatedWork W3211706803 @default.
• W4206961924 hasRelatedWork W4210406818 @default.
• W4206961924 hasRelatedWork W4246942721 @default.
• W4206961924 hasRelatedWork W4289035754 @default.
• W4206961924 hasRelatedWork W4304136894 @default.
• W4206961924 hasRelatedWork W4306779889 @default.
• W4206961924 hasRelatedWork W4382775358 @default.
• W4206961924 hasRelatedWork W4386732777 @default.
• W4206961924 hasVolume "13" @default.
• W4206961924 isParatext "false" @default.

• next