FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2098721803> ?p ?o ?g. }

• W2098721803 endingPage "10534" @default.
• W2098721803 startingPage "10529" @default.
• W2098721803 abstract "This paper is about an algorithm, FlexTree, for general supervised learning. It extends the binary tree-structured approach (Classification and Regression Trees, CART) although it differs greatly in its selection and combination of predictors. It is particularly applicable to assessing interactions: gene by gene and gene by environment as they bear on complex disease. One model for predisposition to complex disease involves many genes. Of them, most are pure noise; each of the values that is not the prevalent genotype for the minority of genes that contribute to the signal carries a “score.” Scores add. Individuals with scores above an unknown threshold are predisposed to the disease. For the additive score problem and simulated data, FlexTree has cross-validated risk better than many cutting-edge technologies to which it was compared when small fractions of candidate genes carry the signal. For the model where only a precise list of aberrant genotypes is predisposing, there is not a systematic pattern of absolute superiority; however, overall, FlexTree seems better than the other technologies. We tried the algorithm on data from 563 Chinese women, 206 hypotensive, 357 hypertensive, with information on ethnicity, menopausal status, insulin-resistant status, and 21 loci. FlexTree and Logic Regression appear better than the others in terms of Bayes risk. However, the differences are not significant in the usual statistical sense." @default.
• W2098721803 created "2016-06-24" @default.
• W2098721803 creator A5018240777 @default.
• W2098721803 creator A5025803819 @default.
• W2098721803 creator A5051232840 @default.
• W2098721803 creator A5051914934 @default.
• W2098721803 creator A5054196214 @default.
• W2098721803 creator A5059469183 @default.
• W2098721803 creator A5068820196 @default.
• W2098721803 creator A5073857588 @default.
• W2098721803 creator A5084795552 @default.
• W2098721803 creator A5085936676 @default.
• W2098721803 creator A5091746380 @default.
• W2098721803 date "2004-07-12" @default.
• W2098721803 modified "2023-10-11" @default.
• W2098721803 title "Tree-structured supervised learning and the genetics of hypertension" @default.
• W2098721803 cites W1774711529 @default.
• W2098721803 cites W1864025888 @default.
• W2098721803 cites W1967610656 @default.
• W2098721803 cites W1971506602 @default.
• W2098721803 cites W1979069430 @default.
• W2098721803 cites W1985469212 @default.
• W2098721803 cites W1994914276 @default.
• W2098721803 cites W2023058928 @default.
• W2098721803 cites W2033210506 @default.
• W2098721803 cites W2118921994 @default.
• W2098721803 cites W2123229219 @default.
• W2098721803 cites W2146308125 @default.
• W2098721803 cites W2151458434 @default.
• W2098721803 cites W2160351402 @default.
• W2098721803 cites W2614633882 @default.
• W2098721803 cites W2911964244 @default.
• W2098721803 cites W40283713 @default.
• W2098721803 cites W4231211138 @default.
• W2098721803 cites W4235011515 @default.
• W2098721803 doi "https://doi.org/10.1073/pnas.0403794101" @default.
• W2098721803 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/489971" @default.
• W2098721803 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/15249660" @default.
• W2098721803 hasPublicationYear "2004" @default.
• W2098721803 type Work @default.
• W2098721803 sameAs 2098721803 @default.
• W2098721803 citedByCount "45" @default.
• W2098721803 countsByYear W20987218032012 @default.
• W2098721803 countsByYear W20987218032013 @default.
• W2098721803 countsByYear W20987218032014 @default.
• W2098721803 countsByYear W20987218032015 @default.
• W2098721803 countsByYear W20987218032016 @default.
• W2098721803 countsByYear W20987218032017 @default.
• W2098721803 countsByYear W20987218032018 @default.
• W2098721803 countsByYear W20987218032019 @default.
• W2098721803 countsByYear W20987218032021 @default.
• W2098721803 crossrefType "journal-article" @default.
• W2098721803 hasAuthorship W2098721803A5018240777 @default.
• W2098721803 hasAuthorship W2098721803A5025803819 @default.
• W2098721803 hasAuthorship W2098721803A5051232840 @default.
• W2098721803 hasAuthorship W2098721803A5051914934 @default.
• W2098721803 hasAuthorship W2098721803A5054196214 @default.
• W2098721803 hasAuthorship W2098721803A5059469183 @default.
• W2098721803 hasAuthorship W2098721803A5068820196 @default.
• W2098721803 hasAuthorship W2098721803A5073857588 @default.
• W2098721803 hasAuthorship W2098721803A5084795552 @default.
• W2098721803 hasAuthorship W2098721803A5085936676 @default.
• W2098721803 hasAuthorship W2098721803A5091746380 @default.
• W2098721803 hasBestOaLocation W20987218032 @default.
• W2098721803 hasConcept C104317684 @default.
• W2098721803 hasConcept C105795698 @default.
• W2098721803 hasConcept C107673813 @default.
• W2098721803 hasConcept C113174947 @default.
• W2098721803 hasConcept C119857082 @default.
• W2098721803 hasConcept C12267149 @default.
• W2098721803 hasConcept C126322002 @default.
• W2098721803 hasConcept C134306372 @default.
• W2098721803 hasConcept C154945302 @default.
• W2098721803 hasConcept C207201462 @default.
• W2098721803 hasConcept C2779134260 @default.
• W2098721803 hasConcept C33923547 @default.
• W2098721803 hasConcept C41008148 @default.
• W2098721803 hasConcept C52001869 @default.
• W2098721803 hasConcept C54355233 @default.
• W2098721803 hasConcept C66905080 @default.
• W2098721803 hasConcept C70721500 @default.
• W2098721803 hasConcept C71924100 @default.
• W2098721803 hasConcept C83546350 @default.
• W2098721803 hasConcept C86803240 @default.
• W2098721803 hasConceptScore W2098721803C104317684 @default.
• W2098721803 hasConceptScore W2098721803C105795698 @default.
• W2098721803 hasConceptScore W2098721803C107673813 @default.
• W2098721803 hasConceptScore W2098721803C113174947 @default.
• W2098721803 hasConceptScore W2098721803C119857082 @default.
• W2098721803 hasConceptScore W2098721803C12267149 @default.
• W2098721803 hasConceptScore W2098721803C126322002 @default.
• W2098721803 hasConceptScore W2098721803C134306372 @default.
• W2098721803 hasConceptScore W2098721803C154945302 @default.
• W2098721803 hasConceptScore W2098721803C207201462 @default.
• W2098721803 hasConceptScore W2098721803C2779134260 @default.
• W2098721803 hasConceptScore W2098721803C33923547 @default.
• W2098721803 hasConceptScore W2098721803C41008148 @default.
• W2098721803 hasConceptScore W2098721803C52001869 @default.

• next