FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4286255699> ?p ?o ?g. }

• W4286255699 endingPage "105806" @default.
• W4286255699 startingPage "105806" @default.
• W4286255699 abstract "In the Coronavirus disease-2019 (COVID-19) pandemic, for fast and accurate diagnosis of a large number of patients, besides traditional methods, automated diagnostic tools are now extremely required. In this paper, a deep convolutional neural network (CNN) based scheme is proposed for automated accurate diagnosis of COVID-19 from lung computed tomography (CT) scan images. First, for the automated segmentation of lung regions in a chest CT scan, a modified CNN architecture, namely SKICU-Net is proposed by incorporating additional skip interconnections in the U-Net model that overcome the loss of information in dimension scaling. Next, an agglomerative hierarchical clustering is deployed to eliminate the CT slices without significant information. Finally, for effective feature extraction and diagnosis of COVID-19 and pneumonia from the segmented lung slices, a modified DenseNet architecture, namely P-DenseCOVNet is designed where parallel convolutional paths are introduced on top of the conventional DenseNet model for getting better performance through overcoming the loss of positional arguments. Outstanding performances have been achieved with an F1 score of 0.97 in the segmentation task along with an accuracy of 87.5% in diagnosing COVID-19, common pneumonia, and normal cases. Significant experimental results and comparison with other studies show that the proposed scheme provides very satisfactory performances and can serve as an effective diagnostic tool in the current pandemic." @default.
• W4286255699 created "2022-07-21" @default.
• W4286255699 creator A5006940459 @default.
• W4286255699 creator A5009603089 @default.
• W4286255699 creator A5014251585 @default.
• W4286255699 creator A5074606314 @default.
• W4286255699 creator A5085857785 @default.
• W4286255699 date "2022-10-01" @default.
• W4286255699 modified "2023-10-01" @default.
• W4286255699 title "A dual-stage deep convolutional neural network for automatic diagnosis of COVID-19 and pneumonia from chest CT images" @default.
• W4286255699 cites W2573089705 @default.
• W4286255699 cites W2791655542 @default.
• W4286255699 cites W2884436604 @default.
• W4286255699 cites W2899279931 @default.
• W4286255699 cites W2920218276 @default.
• W4286255699 cites W2928133111 @default.
• W4286255699 cites W2962731543 @default.
• W4286255699 cites W2962858109 @default.
• W4286255699 cites W2963446712 @default.
• W4286255699 cites W2999318660 @default.
• W4286255699 cites W3001465255 @default.
• W4286255699 cites W3004906315 @default.
• W4286255699 cites W3006110666 @default.
• W4286255699 cites W3007273493 @default.
• W4286255699 cites W3007497549 @default.
• W4286255699 cites W3011149445 @default.
• W4286255699 cites W3012127105 @default.
• W4286255699 cites W3020653337 @default.
• W4286255699 cites W3024575832 @default.
• W4286255699 cites W3026931681 @default.
• W4286255699 cites W3027914507 @default.
• W4286255699 cites W3028070348 @default.
• W4286255699 cites W3037538421 @default.
• W4286255699 cites W3048886990 @default.
• W4286255699 cites W3049510520 @default.
• W4286255699 cites W3096384571 @default.
• W4286255699 cites W3102469298 @default.
• W4286255699 cites W3104810384 @default.
• W4286255699 cites W3125779006 @default.
• W4286255699 cites W3125832420 @default.
• W4286255699 cites W3129576291 @default.
• W4286255699 cites W3129581972 @default.
• W4286255699 cites W3130661843 @default.
• W4286255699 cites W3133191822 @default.
• W4286255699 cites W3133590263 @default.
• W4286255699 cites W3134978274 @default.
• W4286255699 cites W3136933888 @default.
• W4286255699 cites W3198859228 @default.
• W4286255699 cites W4200620098 @default.
• W4286255699 doi "https://doi.org/10.1016/j.compbiomed.2022.105806" @default.
• W4286255699 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35994932" @default.
• W4286255699 hasPublicationYear "2022" @default.
• W4286255699 type Work @default.
• W4286255699 citedByCount "4" @default.
• W4286255699 countsByYear W42862556992023 @default.
• W4286255699 crossrefType "journal-article" @default.
• W4286255699 hasAuthorship W4286255699A5006940459 @default.
• W4286255699 hasAuthorship W4286255699A5009603089 @default.
• W4286255699 hasAuthorship W4286255699A5014251585 @default.
• W4286255699 hasAuthorship W4286255699A5074606314 @default.
• W4286255699 hasAuthorship W4286255699A5085857785 @default.
• W4286255699 hasBestOaLocation W42862556992 @default.
• W4286255699 hasConcept C108583219 @default.
• W4286255699 hasConcept C124101348 @default.
• W4286255699 hasConcept C126322002 @default.
• W4286255699 hasConcept C138885662 @default.
• W4286255699 hasConcept C142724271 @default.
• W4286255699 hasConcept C146357865 @default.
• W4286255699 hasConcept C151730666 @default.
• W4286255699 hasConcept C153180895 @default.
• W4286255699 hasConcept C154945302 @default.
• W4286255699 hasConcept C2776401178 @default.
• W4286255699 hasConcept C2777914695 @default.
• W4286255699 hasConcept C2779134260 @default.
• W4286255699 hasConcept C3008058167 @default.
• W4286255699 hasConcept C41008148 @default.
• W4286255699 hasConcept C41895202 @default.
• W4286255699 hasConcept C524204448 @default.
• W4286255699 hasConcept C52622490 @default.
• W4286255699 hasConcept C71924100 @default.
• W4286255699 hasConcept C73555534 @default.
• W4286255699 hasConcept C81363708 @default.
• W4286255699 hasConcept C86803240 @default.
• W4286255699 hasConcept C89600930 @default.
• W4286255699 hasConceptScore W4286255699C108583219 @default.
• W4286255699 hasConceptScore W4286255699C124101348 @default.
• W4286255699 hasConceptScore W4286255699C126322002 @default.
• W4286255699 hasConceptScore W4286255699C138885662 @default.
• W4286255699 hasConceptScore W4286255699C142724271 @default.
• W4286255699 hasConceptScore W4286255699C146357865 @default.
• W4286255699 hasConceptScore W4286255699C151730666 @default.
• W4286255699 hasConceptScore W4286255699C153180895 @default.
• W4286255699 hasConceptScore W4286255699C154945302 @default.
• W4286255699 hasConceptScore W4286255699C2776401178 @default.
• W4286255699 hasConceptScore W4286255699C2777914695 @default.
• W4286255699 hasConceptScore W4286255699C2779134260 @default.
• W4286255699 hasConceptScore W4286255699C3008058167 @default.
• W4286255699 hasConceptScore W4286255699C41008148 @default.

• next