FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385580905> ?p ?o ?g. }

• W4385580905 abstract "This work aimed to explore the diagnostic value of a deep convolutional neural network (CNN) combined with computed tomography (CT) images in patients with severe pneumonia complicated with pulmonary infection. A total of 120 patients with severe pneumonia complicated by pulmonary infection admitted to the hospital were selected as research subjects and underwent CT imaging scans. The empty convolution (EC) and U-net phase were combined to construct an EC-U-net, which was applied to process the CT images. The results showed that the learning rate of the EC-U-net model decreased substantially with increasing training times until it stabilized and reached zero after 40 training times. The segmentation result of the EC-U-net model for the CT image was very similar to that of the mask image, except for some deviations in edge segmentation. The EC-U-net model exhibited a significantly smaller cross-entropy loss function (CELF) and a higher Dice coefficient than the CNN algorithm. The diagnostic accuracy of CT images based on the EC-U-net model for severe pneumonia complicated with pulmonary infection was substantially higher than that of CT images alone, while the false negative rate (FNR) and false positive rate (FPR) were substantially lower (P < 0.05). Moreover, the true positive rates (TPRs) of CT images based on the EC-U-net model for patchy high-density shadows, diffuse ground glass density shadows, pleural effusion, and lung consolidation were obviously higher than those of the original CT images (P < 0.05). In short, the EC-U-net model was superior to the traditional algorithm regarding the overall performance of CT image segmentation, which can be clinically applied. CT images based on the EC-U-net model can clearly display pulmonary infection lesions, improve the clinical diagnosis of severe pneumonia complicated with pulmonary infection, and help to screen early pulmonary infection and carry out symptomatic treatment." @default.
• W4385580905 created "2023-08-05" @default.
• W4385580905 creator A5035153981 @default.
• W4385580905 creator A5075909513 @default.
• W4385580905 creator A5087766208 @default.
• W4385580905 date "2023-08-04" @default.
• W4385580905 modified "2023-09-25" @default.
• W4385580905 title "Evaluation of computed tomography images under deep learning in the diagnosis of severe pulmonary infection" @default.
• W4385580905 cites W2553421878 @default.
• W4385580905 cites W2800806089 @default.
• W4385580905 cites W2809470868 @default.
• W4385580905 cites W3013371242 @default.
• W4385580905 cites W3016250576 @default.
• W4385580905 cites W3016328037 @default.
• W4385580905 cites W3016513502 @default.
• W4385580905 cites W3017201241 @default.
• W4385580905 cites W3021365959 @default.
• W4385580905 cites W3024836211 @default.
• W4385580905 cites W3031776733 @default.
• W4385580905 cites W3038544108 @default.
• W4385580905 cites W3040561683 @default.
• W4385580905 cites W3043327973 @default.
• W4385580905 cites W3094388274 @default.
• W4385580905 cites W3095784284 @default.
• W4385580905 cites W3112613501 @default.
• W4385580905 cites W3115781494 @default.
• W4385580905 cites W3131729262 @default.
• W4385580905 cites W3180164722 @default.
• W4385580905 cites W3189806772 @default.
• W4385580905 cites W3192851400 @default.
• W4385580905 cites W3197813001 @default.
• W4385580905 cites W3200372794 @default.
• W4385580905 cites W3215026929 @default.
• W4385580905 cites W4200387295 @default.
• W4385580905 cites W4210787000 @default.
• W4385580905 doi "https://doi.org/10.3389/fncom.2023.1115167" @default.
• W4385580905 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37602316" @default.
• W4385580905 hasPublicationYear "2023" @default.
• W4385580905 type Work @default.
• W4385580905 citedByCount "0" @default.
• W4385580905 crossrefType "journal-article" @default.
• W4385580905 hasAuthorship W4385580905A5035153981 @default.
• W4385580905 hasAuthorship W4385580905A5075909513 @default.
• W4385580905 hasAuthorship W4385580905A5087766208 @default.
• W4385580905 hasBestOaLocation W43855809051 @default.
• W4385580905 hasConcept C124504099 @default.
• W4385580905 hasConcept C126322002 @default.
• W4385580905 hasConcept C126838900 @default.
• W4385580905 hasConcept C153180895 @default.
• W4385580905 hasConcept C154945302 @default.
• W4385580905 hasConcept C163892561 @default.
• W4385580905 hasConcept C2777914695 @default.
• W4385580905 hasConcept C2779634585 @default.
• W4385580905 hasConcept C2989005 @default.
• W4385580905 hasConcept C33923547 @default.
• W4385580905 hasConcept C41008148 @default.
• W4385580905 hasConcept C544519230 @default.
• W4385580905 hasConcept C71924100 @default.
• W4385580905 hasConcept C81363708 @default.
• W4385580905 hasConcept C89600930 @default.
• W4385580905 hasConceptScore W4385580905C124504099 @default.
• W4385580905 hasConceptScore W4385580905C126322002 @default.
• W4385580905 hasConceptScore W4385580905C126838900 @default.
• W4385580905 hasConceptScore W4385580905C153180895 @default.
• W4385580905 hasConceptScore W4385580905C154945302 @default.
• W4385580905 hasConceptScore W4385580905C163892561 @default.
• W4385580905 hasConceptScore W4385580905C2777914695 @default.
• W4385580905 hasConceptScore W4385580905C2779634585 @default.
• W4385580905 hasConceptScore W4385580905C2989005 @default.
• W4385580905 hasConceptScore W4385580905C33923547 @default.
• W4385580905 hasConceptScore W4385580905C41008148 @default.
• W4385580905 hasConceptScore W4385580905C544519230 @default.
• W4385580905 hasConceptScore W4385580905C71924100 @default.
• W4385580905 hasConceptScore W4385580905C81363708 @default.
• W4385580905 hasConceptScore W4385580905C89600930 @default.
• W4385580905 hasLocation W43855809051 @default.
• W4385580905 hasLocation W43855809052 @default.
• W4385580905 hasOpenAccess W4385580905 @default.
• W4385580905 hasPrimaryLocation W43855809051 @default.
• W4385580905 hasRelatedWork W2318634999 @default.
• W4385580905 hasRelatedWork W2767651786 @default.
• W4385580905 hasRelatedWork W2769435486 @default.
• W4385580905 hasRelatedWork W2912288872 @default.
• W4385580905 hasRelatedWork W2948809999 @default.
• W4385580905 hasRelatedWork W2969790209 @default.
• W4385580905 hasRelatedWork W4200528772 @default.
• W4385580905 hasRelatedWork W4286545890 @default.
• W4385580905 hasRelatedWork W564581980 @default.
• W4385580905 hasRelatedWork W83375014 @default.
• W4385580905 hasVolume "17" @default.
• W4385580905 isParatext "false" @default.
• W4385580905 isRetracted "false" @default.
• W4385580905 workType "article" @default.