FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3197286338> ?p ?o ?g. }

• W3197286338 endingPage "104835" @default.
• W3197286338 startingPage "104835" @default.
• W3197286338 abstract "The world is significantly affected by infectious coronavirus disease (covid-19). Timely prognosis and treatment are important to control the spread of this infection. Unreliable screening systems and limited number of clinical facilities are the major hurdles in controlling the spread of covid-19. Nowadays, many automated detection systems based on deep learning techniques using computed tomography (CT) images have been proposed to detect covid-19. However, these systems have the following drawbacks: (i) limited data problem poses a major hindrance to train the deep neural network model to provide accurate diagnosis, (ii) random choice of hyperparameters of Convolutional Neural Network (CNN) significantly affects the classification performance, since the hyperparameters have to be application dependent and, (iii) the generalization ability using CNN classification is usually not validated. To address the aforementioned issues, we propose two models: (i) based on a transfer learning approach, and (ii) using novel strategy to optimize the CNN hyperparameters using Whale optimization-based BAT algorithm + AdaBoost classifier built using dynamic ensemble selection techniques. According to our second method depending on the characteristics of test sample, the classifier is chosen, thereby reducing the risk of overfitting and simultaneously produced promising results. Our proposed methodologies are developed using 746 CT images. Our method obtained a sensitivity, specificity, accuracy, F-1 score, and precision of 0.98, 0.97, 0.98, 0.98, and 0.98, respectively with five-fold cross-validation strategy. Our developed prototype is ready to be tested with huge chest CT images database before its real-world application." @default.
• W3197286338 created "2021-09-13" @default.
• W3197286338 creator A5000690812 @default.
• W3197286338 creator A5014241881 @default.
• W3197286338 creator A5015384662 @default.
• W3197286338 creator A5045783666 @default.
• W3197286338 creator A5056139480 @default.
• W3197286338 creator A5078941914 @default.
• W3197286338 date "2021-10-01" @default.
• W3197286338 modified "2023-10-06" @default.
• W3197286338 title "Novel ensemble of optimized CNN and dynamic selection techniques for accurate Covid-19 screening using chest CT images" @default.
• W3197286338 cites W1444952417 @default.
• W3197286338 cites W1988844742 @default.
• W3197286338 cites W2002302337 @default.
• W3197286338 cites W2022306346 @default.
• W3197286338 cites W2145940431 @default.
• W3197286338 cites W2153351685 @default.
• W3197286338 cites W2165466912 @default.
• W3197286338 cites W2290883490 @default.
• W3197286338 cites W2618530766 @default.
• W3197286338 cites W2755371172 @default.
• W3197286338 cites W2923345427 @default.
• W3197286338 cites W3009875419 @default.
• W3197286338 cites W3017644243 @default.
• W3197286338 cites W3019980738 @default.
• W3197286338 cites W3028070348 @default.
• W3197286338 cites W3038744550 @default.
• W3197286338 cites W3046722451 @default.
• W3197286338 cites W3049505831 @default.
• W3197286338 cites W3086462707 @default.
• W3197286338 cites W3092624683 @default.
• W3197286338 cites W3094388274 @default.
• W3197286338 cites W3109192382 @default.
• W3197286338 cites W3129350780 @default.
• W3197286338 cites W3132061261 @default.
• W3197286338 cites W4292083457 @default.
• W3197286338 doi "https://doi.org/10.1016/j.compbiomed.2021.104835" @default.
• W3197286338 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8418990" @default.
• W3197286338 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34508976" @default.
• W3197286338 hasPublicationYear "2021" @default.
• W3197286338 type Work @default.
• W3197286338 sameAs 3197286338 @default.
• W3197286338 citedByCount "14" @default.
• W3197286338 countsByYear W31972863382021 @default.
• W3197286338 countsByYear W31972863382022 @default.
• W3197286338 countsByYear W31972863382023 @default.
• W3197286338 crossrefType "journal-article" @default.
• W3197286338 hasAuthorship W3197286338A5000690812 @default.
• W3197286338 hasAuthorship W3197286338A5014241881 @default.
• W3197286338 hasAuthorship W3197286338A5015384662 @default.
• W3197286338 hasAuthorship W3197286338A5045783666 @default.
• W3197286338 hasAuthorship W3197286338A5056139480 @default.
• W3197286338 hasAuthorship W3197286338A5078941914 @default.
• W3197286338 hasBestOaLocation W31972863381 @default.
• W3197286338 hasConcept C108583219 @default.
• W3197286338 hasConcept C119857082 @default.
• W3197286338 hasConcept C141404830 @default.
• W3197286338 hasConcept C142724271 @default.
• W3197286338 hasConcept C150899416 @default.
• W3197286338 hasConcept C153180895 @default.
• W3197286338 hasConcept C154945302 @default.
• W3197286338 hasConcept C169258074 @default.
• W3197286338 hasConcept C22019652 @default.
• W3197286338 hasConcept C2779134260 @default.
• W3197286338 hasConcept C3008058167 @default.
• W3197286338 hasConcept C41008148 @default.
• W3197286338 hasConcept C45942800 @default.
• W3197286338 hasConcept C50644808 @default.
• W3197286338 hasConcept C524204448 @default.
• W3197286338 hasConcept C71924100 @default.
• W3197286338 hasConcept C81363708 @default.
• W3197286338 hasConcept C8642999 @default.
• W3197286338 hasConcept C95623464 @default.
• W3197286338 hasConceptScore W3197286338C108583219 @default.
• W3197286338 hasConceptScore W3197286338C119857082 @default.
• W3197286338 hasConceptScore W3197286338C141404830 @default.
• W3197286338 hasConceptScore W3197286338C142724271 @default.
• W3197286338 hasConceptScore W3197286338C150899416 @default.
• W3197286338 hasConceptScore W3197286338C153180895 @default.
• W3197286338 hasConceptScore W3197286338C154945302 @default.
• W3197286338 hasConceptScore W3197286338C169258074 @default.
• W3197286338 hasConceptScore W3197286338C22019652 @default.
• W3197286338 hasConceptScore W3197286338C2779134260 @default.
• W3197286338 hasConceptScore W3197286338C3008058167 @default.
• W3197286338 hasConceptScore W3197286338C41008148 @default.
• W3197286338 hasConceptScore W3197286338C45942800 @default.
• W3197286338 hasConceptScore W3197286338C50644808 @default.
• W3197286338 hasConceptScore W3197286338C524204448 @default.
• W3197286338 hasConceptScore W3197286338C71924100 @default.
• W3197286338 hasConceptScore W3197286338C81363708 @default.
• W3197286338 hasConceptScore W3197286338C8642999 @default.
• W3197286338 hasConceptScore W3197286338C95623464 @default.
• W3197286338 hasLocation W31972863381 @default.
• W3197286338 hasLocation W31972863382 @default.
• W3197286338 hasLocation W31972863383 @default.
• W3197286338 hasOpenAccess W3197286338 @default.
• W3197286338 hasPrimaryLocation W31972863381 @default.
• W3197286338 hasRelatedWork W1038900426 @default.

• next