Matches in SemOpenAlex for { <https://semopenalex.org/work/W4320727567> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W4320727567 endingPage "42" @default.
- W4320727567 startingPage "42" @default.
- W4320727567 abstract "A rapidly spreading epidemic, COVID-19 had a serious effect on millions and took many lives. Therefore, for individuals with COVID-19, early discovery is essential for halting the infection's progress. To quickly and accurately diagnose COVID-19, imaging modalities, including computed tomography (CT) scans and chest X-ray radiographs, are frequently employed. The potential of artificial intelligence (AI) approaches further explored the creation of automated and precise COVID-19 detection systems. Scientists widely use deep learning techniques to identify coronavirus infection in lung imaging. In our paper, we developed a novel light CNN model architecture with watershed-based region-growing segmentation on Chest X-rays. Both CT scans and X-ray radiographs were employed along with 5-fold cross-validation. Compared to earlier state-of-the-art models, our model is lighter and outperformed the previous methods by achieving a mean accuracy of 98.8% on X-ray images and 98.6% on CT scans, predicting the rate of 0.99% and 0.97% for PPV (Positive predicted Value) and NPV (Negative predicted Value) rate of 0.98% and 0.99%, respectively." @default.
- W4320727567 created "2023-02-15" @default.
- W4320727567 creator A5020665379 @default.
- W4320727567 creator A5059043808 @default.
- W4320727567 creator A5062523981 @default.
- W4320727567 creator A5083936003 @default.
- W4320727567 date "2023-02-13" @default.
- W4320727567 modified "2023-09-26" @default.
- W4320727567 title "Novel Light Convolutional Neural Network for COVID Detection with Watershed Based Region Growing Segmentation" @default.
- W4320727567 cites W3013277995 @default.
- W4320727567 cites W3140022118 @default.
- W4320727567 cites W3209181060 @default.
- W4320727567 cites W3214767560 @default.
- W4320727567 cites W4206067856 @default.
- W4320727567 cites W4206608885 @default.
- W4320727567 cites W4210530275 @default.
- W4320727567 cites W4210613509 @default.
- W4320727567 cites W4213005330 @default.
- W4320727567 cites W4214569887 @default.
- W4320727567 cites W4214656236 @default.
- W4320727567 cites W4220656052 @default.
- W4320727567 cites W4221046732 @default.
- W4320727567 cites W4221086917 @default.
- W4320727567 cites W4226216100 @default.
- W4320727567 cites W4280493037 @default.
- W4320727567 doi "https://doi.org/10.3390/jimaging9020042" @default.
- W4320727567 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36826961" @default.
- W4320727567 hasPublicationYear "2023" @default.
- W4320727567 type Work @default.
- W4320727567 citedByCount "0" @default.
- W4320727567 crossrefType "journal-article" @default.
- W4320727567 hasAuthorship W4320727567A5020665379 @default.
- W4320727567 hasAuthorship W4320727567A5059043808 @default.
- W4320727567 hasAuthorship W4320727567A5062523981 @default.
- W4320727567 hasAuthorship W4320727567A5083936003 @default.
- W4320727567 hasBestOaLocation W43207275671 @default.
- W4320727567 hasConcept C108583219 @default.
- W4320727567 hasConcept C116675565 @default.
- W4320727567 hasConcept C126838900 @default.
- W4320727567 hasConcept C142724271 @default.
- W4320727567 hasConcept C150547873 @default.
- W4320727567 hasConcept C153180895 @default.
- W4320727567 hasConcept C154945302 @default.
- W4320727567 hasConcept C2779134260 @default.
- W4320727567 hasConcept C2989005 @default.
- W4320727567 hasConcept C3006700255 @default.
- W4320727567 hasConcept C3007834351 @default.
- W4320727567 hasConcept C3008058167 @default.
- W4320727567 hasConcept C31972630 @default.
- W4320727567 hasConcept C36454342 @default.
- W4320727567 hasConcept C41008148 @default.
- W4320727567 hasConcept C524204448 @default.
- W4320727567 hasConcept C544519230 @default.
- W4320727567 hasConcept C71924100 @default.
- W4320727567 hasConcept C81363708 @default.
- W4320727567 hasConcept C89600930 @default.
- W4320727567 hasConceptScore W4320727567C108583219 @default.
- W4320727567 hasConceptScore W4320727567C116675565 @default.
- W4320727567 hasConceptScore W4320727567C126838900 @default.
- W4320727567 hasConceptScore W4320727567C142724271 @default.
- W4320727567 hasConceptScore W4320727567C150547873 @default.
- W4320727567 hasConceptScore W4320727567C153180895 @default.
- W4320727567 hasConceptScore W4320727567C154945302 @default.
- W4320727567 hasConceptScore W4320727567C2779134260 @default.
- W4320727567 hasConceptScore W4320727567C2989005 @default.
- W4320727567 hasConceptScore W4320727567C3006700255 @default.
- W4320727567 hasConceptScore W4320727567C3007834351 @default.
- W4320727567 hasConceptScore W4320727567C3008058167 @default.
- W4320727567 hasConceptScore W4320727567C31972630 @default.
- W4320727567 hasConceptScore W4320727567C36454342 @default.
- W4320727567 hasConceptScore W4320727567C41008148 @default.
- W4320727567 hasConceptScore W4320727567C524204448 @default.
- W4320727567 hasConceptScore W4320727567C544519230 @default.
- W4320727567 hasConceptScore W4320727567C71924100 @default.
- W4320727567 hasConceptScore W4320727567C81363708 @default.
- W4320727567 hasConceptScore W4320727567C89600930 @default.
- W4320727567 hasIssue "2" @default.
- W4320727567 hasLocation W43207275671 @default.
- W4320727567 hasLocation W43207275672 @default.
- W4320727567 hasLocation W43207275673 @default.
- W4320727567 hasOpenAccess W4320727567 @default.
- W4320727567 hasPrimaryLocation W43207275671 @default.
- W4320727567 hasRelatedWork W3009669391 @default.
- W4320727567 hasRelatedWork W3036314732 @default.
- W4320727567 hasRelatedWork W3040868419 @default.
- W4320727567 hasRelatedWork W3176864053 @default.
- W4320727567 hasRelatedWork W3198183218 @default.
- W4320727567 hasRelatedWork W4200329650 @default.
- W4320727567 hasRelatedWork W4205317059 @default.
- W4320727567 hasRelatedWork W4206669628 @default.
- W4320727567 hasRelatedWork W4382894326 @default.
- W4320727567 hasRelatedWork W3127156785 @default.
- W4320727567 hasVolume "9" @default.
- W4320727567 isParatext "false" @default.
- W4320727567 isRetracted "false" @default.
- W4320727567 workType "article" @default.