FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4283762661> ?p ?o ?g. }

• W4283762661 endingPage "11" @default.
• W4283762661 startingPage "1" @default.
• W4283762661 abstract "Oral cancer is one of the lethal diseases among the available malignant tumors globally, and it has become a challenging health issue in developing and low-to-middle income countries. The prognosis of oral cancer remains poor because over 50% of patients are recognized at advanced stages. Earlier detection and screening models for oral cancer are mainly based on experts’ knowledge, and it necessitates an automated tool for oral cancer detection. The recent developments of computational intelligence (CI) and computer vision-based approaches help to accomplish enhanced performance in medical-image-related tasks. This article develops an intelligent deep learning enabled oral squamous cell carcinoma detection and classification (IDL-OSCDC) technique using biomedical images. The presented IDL-OSCDC model involves the recognition and classification of oral cancer on biomedical images. The proposed IDL-OSCDC model employs Gabor filtering (GF) as a preprocessing step to eliminate noise content. In addition, the NasNet model is exploited for the generation of high-level deep features from the input images. Moreover, an enhanced grasshopper optimization algorithm (EGOA)-based deep belief network (DBN) model is employed for oral cancer detection and classification. The hyperparameter tuning of the DBN model is performed using the EGOA algorithm which in turn boosts the classification outcomes. The experimentation outcomes of the IDL-OSCDC model using a benchmark biomedical imaging dataset highlighted its promising performance over the other methods with maximum <math xmlns=http://www.w3.org/1998/Math/MathML id=M1> <msub> <mrow> <mtext>accu</mtext> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </math> , <math xmlns=http://www.w3.org/1998/Math/MathML id=M2> <msub> <mrow> <mtext>prec</mtext> </mrow> <mrow> <mi>n</mi> </mrow> </msub> </math> , <math xmlns=http://www.w3.org/1998/Math/MathML id=M3> <msub> <mrow> <mtext>reca</mtext> </mrow> <mrow> <mi>l</mi> </mrow> </msub> </math> , and <math xmlns=http://www.w3.org/1998/Math/MathML id=M4> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mtext>score</mtext> </mrow> </msub> </math> of 95%, 96.15%, 93.75%, and 94.67% correspondingly." @default.
• W4283762661 created "2022-07-02" @default.
• W4283762661 creator A5028169967 @default.
• W4283762661 creator A5054119243 @default.
• W4283762661 creator A5056714732 @default.
• W4283762661 creator A5075183774 @default.
• W4283762661 creator A5091017399 @default.
• W4283762661 date "2022-06-30" @default.
• W4283762661 modified "2023-10-18" @default.
• W4283762661 title "Intelligent Deep Learning Enabled Oral Squamous Cell Carcinoma Detection and Classification Using Biomedical Images" @default.
• W4283762661 cites W2896469379 @default.
• W4283762661 cites W2999351245 @default.
• W4283762661 cites W3018833108 @default.
• W4283762661 cites W3034112021 @default.
• W4283762661 cites W3044073403 @default.
• W4283762661 cites W3046285857 @default.
• W4283762661 cites W3085802240 @default.
• W4283762661 cites W3095677657 @default.
• W4283762661 cites W3105159713 @default.
• W4283762661 cites W3107263686 @default.
• W4283762661 cites W3120074042 @default.
• W4283762661 cites W3138644639 @default.
• W4283762661 cites W3192909153 @default.
• W4283762661 cites W3208020934 @default.
• W4283762661 cites W3213720887 @default.
• W4283762661 cites W4205359793 @default.
• W4283762661 cites W4206443915 @default.
• W4283762661 cites W4210280466 @default.
• W4283762661 cites W4210687304 @default.
• W4283762661 cites W4214659017 @default.
• W4283762661 cites W4214830197 @default.
• W4283762661 doi "https://doi.org/10.1155/2022/7643967" @default.
• W4283762661 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35814555" @default.
• W4283762661 hasPublicationYear "2022" @default.
• W4283762661 type Work @default.
• W4283762661 citedByCount "2" @default.
• W4283762661 countsByYear W42837626612023 @default.
• W4283762661 crossrefType "journal-article" @default.
• W4283762661 hasAuthorship W4283762661A5028169967 @default.
• W4283762661 hasAuthorship W4283762661A5054119243 @default.
• W4283762661 hasAuthorship W4283762661A5056714732 @default.
• W4283762661 hasAuthorship W4283762661A5075183774 @default.
• W4283762661 hasAuthorship W4283762661A5091017399 @default.
• W4283762661 hasBestOaLocation W42837626611 @default.
• W4283762661 hasConcept C108583219 @default.
• W4283762661 hasConcept C119857082 @default.
• W4283762661 hasConcept C121608353 @default.
• W4283762661 hasConcept C126322002 @default.
• W4283762661 hasConcept C13280743 @default.
• W4283762661 hasConcept C154945302 @default.
• W4283762661 hasConcept C185798385 @default.
• W4283762661 hasConcept C205649164 @default.
• W4283762661 hasConcept C34736171 @default.
• W4283762661 hasConcept C41008148 @default.
• W4283762661 hasConcept C71924100 @default.
• W4283762661 hasConcept C97385483 @default.
• W4283762661 hasConceptScore W4283762661C108583219 @default.
• W4283762661 hasConceptScore W4283762661C119857082 @default.
• W4283762661 hasConceptScore W4283762661C121608353 @default.
• W4283762661 hasConceptScore W4283762661C126322002 @default.
• W4283762661 hasConceptScore W4283762661C13280743 @default.
• W4283762661 hasConceptScore W4283762661C154945302 @default.
• W4283762661 hasConceptScore W4283762661C185798385 @default.
• W4283762661 hasConceptScore W4283762661C205649164 @default.
• W4283762661 hasConceptScore W4283762661C34736171 @default.
• W4283762661 hasConceptScore W4283762661C41008148 @default.
• W4283762661 hasConceptScore W4283762661C71924100 @default.
• W4283762661 hasConceptScore W4283762661C97385483 @default.
• W4283762661 hasFunder F4320324047 @default.
• W4283762661 hasLocation W42837626611 @default.
• W4283762661 hasLocation W42837626612 @default.
• W4283762661 hasLocation W42837626613 @default.
• W4283762661 hasOpenAccess W4283762661 @default.
• W4283762661 hasPrimaryLocation W42837626611 @default.
• W4283762661 hasRelatedWork W1501213224 @default.
• W4283762661 hasRelatedWork W2126887587 @default.
• W4283762661 hasRelatedWork W2795261237 @default.
• W4283762661 hasRelatedWork W3082895349 @default.
• W4283762661 hasRelatedWork W3123344745 @default.
• W4283762661 hasRelatedWork W4210841218 @default.
• W4283762661 hasRelatedWork W4223943233 @default.
• W4283762661 hasRelatedWork W4302303815 @default.
• W4283762661 hasRelatedWork W4312200629 @default.
• W4283762661 hasRelatedWork W4380075502 @default.
• W4283762661 hasVolume "2022" @default.
• W4283762661 isParatext "false" @default.
• W4283762661 isRetracted "false" @default.
• W4283762661 workType "article" @default.