Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385628846> ?p ?o ?g. }
- W4385628846 abstract "Machine learning techniques are increasingly embraced in neuroimaging studies of healthy and diseased human brains. They have been used successfully in predicting phenotypes, or even clinical outcomes, and in turning functional connectome metrics into phenotype biomarkers of both healthy individuals and patients. In this study, we used functional connectivity characteristics based on resting state functional magnetic resonance imaging data to accurately classify healthy elderly in terms of their phenotype status. Additionally, as the functional connections that contribute to the classification can be identified, we can draw inferences about the network that is predictive of the investigated phenotypes. Our proposed pipeline for phenotype classification can be expanded to other phenotypes (cognitive, psychological, clinical) and possibly be used to shed light on the modifiable risk and protective factors in normative and pathological brain aging." @default.
- W4385628846 created "2023-08-08" @default.
- W4385628846 creator A5022490304 @default.
- W4385628846 creator A5092836546 @default.
- W4385628846 creator A5092836547 @default.
- W4385628846 date "2023-08-07" @default.
- W4385628846 modified "2023-09-23" @default.
- W4385628846 title "Predicting phenotypes of elderly from resting state fMRI" @default.
- W4385628846 cites W1849775727 @default.
- W4385628846 cites W1906883763 @default.
- W4385628846 cites W1924727730 @default.
- W4385628846 cites W1969845534 @default.
- W4385628846 cites W1970695058 @default.
- W4385628846 cites W1972169949 @default.
- W4385628846 cites W1983208069 @default.
- W4385628846 cites W1990392898 @default.
- W4385628846 cites W1994099567 @default.
- W4385628846 cites W1995964833 @default.
- W4385628846 cites W2091465235 @default.
- W4385628846 cites W2102636708 @default.
- W4385628846 cites W2105435743 @default.
- W4385628846 cites W2111902267 @default.
- W4385628846 cites W2136022845 @default.
- W4385628846 cites W2137229374 @default.
- W4385628846 cites W2151481745 @default.
- W4385628846 cites W2151591509 @default.
- W4385628846 cites W2154848358 @default.
- W4385628846 cites W2174056659 @default.
- W4385628846 cites W2338986748 @default.
- W4385628846 cites W2339955272 @default.
- W4385628846 cites W2427255235 @default.
- W4385628846 cites W2510306587 @default.
- W4385628846 cites W2530303434 @default.
- W4385628846 cites W2552208519 @default.
- W4385628846 cites W2571234872 @default.
- W4385628846 cites W2590328111 @default.
- W4385628846 cites W2602552939 @default.
- W4385628846 cites W2743773590 @default.
- W4385628846 cites W2784262759 @default.
- W4385628846 cites W2793779161 @default.
- W4385628846 cites W2886027299 @default.
- W4385628846 cites W2890996272 @default.
- W4385628846 cites W2892013400 @default.
- W4385628846 cites W2893411620 @default.
- W4385628846 cites W2896555885 @default.
- W4385628846 cites W2951042025 @default.
- W4385628846 cites W2951617899 @default.
- W4385628846 cites W2952991498 @default.
- W4385628846 cites W2954019805 @default.
- W4385628846 cites W2954390085 @default.
- W4385628846 cites W3012066680 @default.
- W4385628846 cites W3038352849 @default.
- W4385628846 cites W3041046627 @default.
- W4385628846 cites W3046275966 @default.
- W4385628846 cites W3111446413 @default.
- W4385628846 cites W3127339500 @default.
- W4385628846 cites W3207397300 @default.
- W4385628846 cites W4210322009 @default.
- W4385628846 cites W4281936745 @default.
- W4385628846 cites W4289527174 @default.
- W4385628846 cites W4294817486 @default.
- W4385628846 cites W4321327237 @default.
- W4385628846 doi "https://doi.org/10.21203/rs.3.rs-3201603/v1" @default.
- W4385628846 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37609310" @default.
- W4385628846 hasPublicationYear "2023" @default.
- W4385628846 type Work @default.
- W4385628846 citedByCount "0" @default.
- W4385628846 crossrefType "posted-content" @default.
- W4385628846 hasAuthorship W4385628846A5022490304 @default.
- W4385628846 hasAuthorship W4385628846A5092836546 @default.
- W4385628846 hasAuthorship W4385628846A5092836547 @default.
- W4385628846 hasBestOaLocation W43856288461 @default.
- W4385628846 hasConcept C104317684 @default.
- W4385628846 hasConcept C111472728 @default.
- W4385628846 hasConcept C127716648 @default.
- W4385628846 hasConcept C138885662 @default.
- W4385628846 hasConcept C142724271 @default.
- W4385628846 hasConcept C15744967 @default.
- W4385628846 hasConcept C169760540 @default.
- W4385628846 hasConcept C169900460 @default.
- W4385628846 hasConcept C207886595 @default.
- W4385628846 hasConcept C2779226451 @default.
- W4385628846 hasConcept C3018011982 @default.
- W4385628846 hasConcept C3020646490 @default.
- W4385628846 hasConcept C44725695 @default.
- W4385628846 hasConcept C45715564 @default.
- W4385628846 hasConcept C54355233 @default.
- W4385628846 hasConcept C58693492 @default.
- W4385628846 hasConcept C66324658 @default.
- W4385628846 hasConcept C71924100 @default.
- W4385628846 hasConcept C86803240 @default.
- W4385628846 hasConcept C97820695 @default.
- W4385628846 hasConceptScore W4385628846C104317684 @default.
- W4385628846 hasConceptScore W4385628846C111472728 @default.
- W4385628846 hasConceptScore W4385628846C127716648 @default.
- W4385628846 hasConceptScore W4385628846C138885662 @default.
- W4385628846 hasConceptScore W4385628846C142724271 @default.
- W4385628846 hasConceptScore W4385628846C15744967 @default.
- W4385628846 hasConceptScore W4385628846C169760540 @default.
- W4385628846 hasConceptScore W4385628846C169900460 @default.