Matches in SemOpenAlex for { <https://semopenalex.org/work/W3212163365> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3212163365 endingPage "4042" @default.
- W3212163365 startingPage "4028" @default.
- W3212163365 abstract "Microarray dataset is one of the biological databases that contains huge quantity of gene expression data. It is predominantly used in storing maximum biological information that is related to the measurements, search criteria and real-time data required for predicting hard-hitting diseases like Lung Cancer. The Microarray dataset comprised of complex data with enormous biological features that are complicated to be analyzed and interpreted for prediction of diseases with high efficiency. The major ardent of this paper is to review the various existing microarray datasets and techniques applied in prediction of Non-Small Cell Lung Cancer (NSCLC). The paper further explores the various existing feature selection models available in microarray datasets with their tools and techniques applied for prediction. A review on High Dimensionality Reduction (HDR) in microarray datasets was proposed and the significant methods with the algorithms was studied. The assessment was conducted based on various research works conducted during the period from 2016 to 2020. The evaluation methods like accuracy, f-score and other measures to test the level of performance was presented. The research gaps pertaining to the current research scenario has been analyzed and presented with tabulated analysis. The review analysis identified that feature extraction and HDR are highly essential for efficient normalization of microarray datasets in efficient prediction of NSCLC at the earliest stage possible. The recommended suggestions ordained that the microarray dataset preprocessing and feature analysis required novel frameworks for better outcomes in the future perspectives of Lung cancer predictions." @default.
- W3212163365 created "2021-11-22" @default.
- W3212163365 creator A5057285872 @default.
- W3212163365 creator A5086991547 @default.
- W3212163365 date "2021-11-04" @default.
- W3212163365 modified "2023-09-23" @default.
- W3212163365 title "Review on Feature Selection Methods and High Dimensionality Reduction Techniques with Microarray Datasets in Early Prediction of Lung Cancer" @default.
- W3212163365 hasPublicationYear "2021" @default.
- W3212163365 type Work @default.
- W3212163365 sameAs 3212163365 @default.
- W3212163365 citedByCount "0" @default.
- W3212163365 crossrefType "journal-article" @default.
- W3212163365 hasAuthorship W3212163365A5057285872 @default.
- W3212163365 hasAuthorship W3212163365A5086991547 @default.
- W3212163365 hasConcept C104317684 @default.
- W3212163365 hasConcept C10551718 @default.
- W3212163365 hasConcept C111030470 @default.
- W3212163365 hasConcept C119857082 @default.
- W3212163365 hasConcept C124101348 @default.
- W3212163365 hasConcept C136886441 @default.
- W3212163365 hasConcept C138885662 @default.
- W3212163365 hasConcept C144024400 @default.
- W3212163365 hasConcept C148483581 @default.
- W3212163365 hasConcept C150194340 @default.
- W3212163365 hasConcept C154945302 @default.
- W3212163365 hasConcept C186836561 @default.
- W3212163365 hasConcept C19165224 @default.
- W3212163365 hasConcept C24361400 @default.
- W3212163365 hasConcept C2776401178 @default.
- W3212163365 hasConcept C34736171 @default.
- W3212163365 hasConcept C41008148 @default.
- W3212163365 hasConcept C41895202 @default.
- W3212163365 hasConcept C548314002 @default.
- W3212163365 hasConcept C55493867 @default.
- W3212163365 hasConcept C70518039 @default.
- W3212163365 hasConcept C8415881 @default.
- W3212163365 hasConcept C86803240 @default.
- W3212163365 hasConceptScore W3212163365C104317684 @default.
- W3212163365 hasConceptScore W3212163365C10551718 @default.
- W3212163365 hasConceptScore W3212163365C111030470 @default.
- W3212163365 hasConceptScore W3212163365C119857082 @default.
- W3212163365 hasConceptScore W3212163365C124101348 @default.
- W3212163365 hasConceptScore W3212163365C136886441 @default.
- W3212163365 hasConceptScore W3212163365C138885662 @default.
- W3212163365 hasConceptScore W3212163365C144024400 @default.
- W3212163365 hasConceptScore W3212163365C148483581 @default.
- W3212163365 hasConceptScore W3212163365C150194340 @default.
- W3212163365 hasConceptScore W3212163365C154945302 @default.
- W3212163365 hasConceptScore W3212163365C186836561 @default.
- W3212163365 hasConceptScore W3212163365C19165224 @default.
- W3212163365 hasConceptScore W3212163365C24361400 @default.
- W3212163365 hasConceptScore W3212163365C2776401178 @default.
- W3212163365 hasConceptScore W3212163365C34736171 @default.
- W3212163365 hasConceptScore W3212163365C41008148 @default.
- W3212163365 hasConceptScore W3212163365C41895202 @default.
- W3212163365 hasConceptScore W3212163365C548314002 @default.
- W3212163365 hasConceptScore W3212163365C55493867 @default.
- W3212163365 hasConceptScore W3212163365C70518039 @default.
- W3212163365 hasConceptScore W3212163365C8415881 @default.
- W3212163365 hasConceptScore W3212163365C86803240 @default.
- W3212163365 hasIssue "1" @default.
- W3212163365 hasLocation W32121633651 @default.
- W3212163365 hasOpenAccess W3212163365 @default.
- W3212163365 hasPrimaryLocation W32121633651 @default.
- W3212163365 hasRelatedWork W1826817635 @default.
- W3212163365 hasRelatedWork W2019446952 @default.
- W3212163365 hasRelatedWork W2065372064 @default.
- W3212163365 hasRelatedWork W2079472110 @default.
- W3212163365 hasRelatedWork W2081800569 @default.
- W3212163365 hasRelatedWork W2106574346 @default.
- W3212163365 hasRelatedWork W2113820893 @default.
- W3212163365 hasRelatedWork W2114714796 @default.
- W3212163365 hasRelatedWork W2116960904 @default.
- W3212163365 hasRelatedWork W2131822674 @default.
- W3212163365 hasRelatedWork W2364642767 @default.
- W3212163365 hasRelatedWork W2487235311 @default.
- W3212163365 hasRelatedWork W2536410897 @default.
- W3212163365 hasRelatedWork W2944891972 @default.
- W3212163365 hasRelatedWork W2945949212 @default.
- W3212163365 hasRelatedWork W2974677792 @default.
- W3212163365 hasRelatedWork W3086507350 @default.
- W3212163365 hasRelatedWork W77957372 @default.
- W3212163365 hasRelatedWork W947671513 @default.
- W3212163365 hasRelatedWork W2144972194 @default.
- W3212163365 hasVolume "10" @default.
- W3212163365 isParatext "false" @default.
- W3212163365 isRetracted "false" @default.
- W3212163365 magId "3212163365" @default.
- W3212163365 workType "article" @default.