Matches in SemOpenAlex for { <https://semopenalex.org/work/W3110842668> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W3110842668 endingPage "28" @default.
- W3110842668 startingPage "19" @default.
- W3110842668 abstract "Metagenomic is now a novel source for supporting diagnosis and prognosis human diseases. Numerous studies have pointed to crucial roles of metagenomics in personalized medicine approaches. Recent years, machine learning has been widely deploying in a vast amount of metagenomic research. Usually, gene family data are characterized by very high dimension which can be up to millions of features. However, the number of obtained samples is rather small compared to the number of attributes. Therefore, the results in validation sets often exhibit poor performance while we can get high accuracy during training phrases. Moreover, a very large number of features on each gene family dataset consumes a considerable time in processing and learning. In this study, we propose feature selection methods using Ridge Regression on datasets including gene families, then the new obtained set of features is binned by an equal width binning approach and fetched into either a Linear Regression and a One-Dimensional Convolutional Neural Network (CNN1D) to do prediction tasks. The experiments are examined on more than 1000 samples of gene family abundance datasets related to Liver Cirrhosis, Colorectal Cancer, Inflammatory Bowel Disease, Obesity and Type 2 Diabetes. The results from the proposed method combining between feature selection algorithms and binning show significant improvements in both prediction performance and execution time compared to the state-of-the-art methods." @default.
- W3110842668 created "2020-12-21" @default.
- W3110842668 creator A5002976920 @default.
- W3110842668 creator A5018364584 @default.
- W3110842668 creator A5032080842 @default.
- W3110842668 creator A5053444037 @default.
- W3110842668 creator A5060017962 @default.
- W3110842668 creator A5069032340 @default.
- W3110842668 creator A5070531776 @default.
- W3110842668 date "2020-12-08" @default.
- W3110842668 modified "2023-09-24" @default.
- W3110842668 title "Effective Disease Prediction on Gene Family Abundance Using Feature Selection and Binning Approach" @default.
- W3110842668 cites W1703384511 @default.
- W3110842668 cites W1756788811 @default.
- W3110842668 cites W1964027278 @default.
- W3110842668 cites W1964042173 @default.
- W3110842668 cites W2004549986 @default.
- W3110842668 cites W2033157818 @default.
- W3110842668 cites W2071841602 @default.
- W3110842668 cites W2100080086 @default.
- W3110842668 cites W2122825543 @default.
- W3110842668 cites W2125826054 @default.
- W3110842668 cites W2130725058 @default.
- W3110842668 cites W2144430639 @default.
- W3110842668 cites W2147783737 @default.
- W3110842668 cites W2170951896 @default.
- W3110842668 cites W2171571559 @default.
- W3110842668 cites W2406298684 @default.
- W3110842668 cites W2473355215 @default.
- W3110842668 cites W2475358754 @default.
- W3110842668 cites W2991464892 @default.
- W3110842668 doi "https://doi.org/10.1007/978-981-15-9354-3_2" @default.
- W3110842668 hasPublicationYear "2020" @default.
- W3110842668 type Work @default.
- W3110842668 sameAs 3110842668 @default.
- W3110842668 citedByCount "1" @default.
- W3110842668 countsByYear W31108426682023 @default.
- W3110842668 crossrefType "book-chapter" @default.
- W3110842668 hasAuthorship W3110842668A5002976920 @default.
- W3110842668 hasAuthorship W3110842668A5018364584 @default.
- W3110842668 hasAuthorship W3110842668A5032080842 @default.
- W3110842668 hasAuthorship W3110842668A5053444037 @default.
- W3110842668 hasAuthorship W3110842668A5060017962 @default.
- W3110842668 hasAuthorship W3110842668A5069032340 @default.
- W3110842668 hasAuthorship W3110842668A5070531776 @default.
- W3110842668 hasConcept C104317684 @default.
- W3110842668 hasConcept C105795698 @default.
- W3110842668 hasConcept C119857082 @default.
- W3110842668 hasConcept C124101348 @default.
- W3110842668 hasConcept C138885662 @default.
- W3110842668 hasConcept C148483581 @default.
- W3110842668 hasConcept C15151743 @default.
- W3110842668 hasConcept C153180895 @default.
- W3110842668 hasConcept C154945302 @default.
- W3110842668 hasConcept C2776401178 @default.
- W3110842668 hasConcept C33923547 @default.
- W3110842668 hasConcept C41008148 @default.
- W3110842668 hasConcept C41895202 @default.
- W3110842668 hasConcept C54355233 @default.
- W3110842668 hasConcept C81363708 @default.
- W3110842668 hasConcept C81917197 @default.
- W3110842668 hasConcept C83546350 @default.
- W3110842668 hasConcept C86803240 @default.
- W3110842668 hasConceptScore W3110842668C104317684 @default.
- W3110842668 hasConceptScore W3110842668C105795698 @default.
- W3110842668 hasConceptScore W3110842668C119857082 @default.
- W3110842668 hasConceptScore W3110842668C124101348 @default.
- W3110842668 hasConceptScore W3110842668C138885662 @default.
- W3110842668 hasConceptScore W3110842668C148483581 @default.
- W3110842668 hasConceptScore W3110842668C15151743 @default.
- W3110842668 hasConceptScore W3110842668C153180895 @default.
- W3110842668 hasConceptScore W3110842668C154945302 @default.
- W3110842668 hasConceptScore W3110842668C2776401178 @default.
- W3110842668 hasConceptScore W3110842668C33923547 @default.
- W3110842668 hasConceptScore W3110842668C41008148 @default.
- W3110842668 hasConceptScore W3110842668C41895202 @default.
- W3110842668 hasConceptScore W3110842668C54355233 @default.
- W3110842668 hasConceptScore W3110842668C81363708 @default.
- W3110842668 hasConceptScore W3110842668C81917197 @default.
- W3110842668 hasConceptScore W3110842668C83546350 @default.
- W3110842668 hasConceptScore W3110842668C86803240 @default.
- W3110842668 hasLocation W31108426681 @default.
- W3110842668 hasOpenAccess W3110842668 @default.
- W3110842668 hasPrimaryLocation W31108426681 @default.
- W3110842668 hasRelatedWork W2767651786 @default.
- W3110842668 hasRelatedWork W2886673456 @default.
- W3110842668 hasRelatedWork W2912288872 @default.
- W3110842668 hasRelatedWork W3021430260 @default.
- W3110842668 hasRelatedWork W3027997911 @default.
- W3110842668 hasRelatedWork W3106036237 @default.
- W3110842668 hasRelatedWork W4287776258 @default.
- W3110842668 hasRelatedWork W4293525103 @default.
- W3110842668 hasRelatedWork W564581980 @default.
- W3110842668 hasRelatedWork W2345184372 @default.
- W3110842668 isParatext "false" @default.
- W3110842668 isRetracted "false" @default.
- W3110842668 magId "3110842668" @default.
- W3110842668 workType "book-chapter" @default.