Matches in SemOpenAlex for { <https://semopenalex.org/work/W2986797487> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W2986797487 endingPage "48" @default.
- W2986797487 startingPage "44" @default.
- W2986797487 abstract "Brain age prediction is a machine learning method that estimates an individual's chronological age from their neuroimaging scans. Brain age indicates whether an individual's brain appears than age-matched healthy peers, suggesting that they may have experienced a higher cumulative exposure to brain insults or were more impacted by those pathological insults. However, contemporary brain age models include older participants with amyloid pathology in their training sets and thus may be confounded when studying Alzheimer's disease (AD). We showed that amyloid status is a critical feature for brain age prediction models. We trained a model on T1-weighted MRI images participants without amyloid pathology. MRI data were processed to estimate gray matter density voxel-wise, which were then used to predict chronological age. Our model performed accurately comparable to previous models. Notably, we demonstrated more significant differences between AD diagnostic groups than other models. In addition, our model was able to delineate significant differences in brain age relative to chronological age between cognitively normal individuals with and without amyloid. Incorporation of amyloid status in brain age prediction models ultimately improves the utility of brain age as a biomarker for AD." @default.
- W2986797487 created "2019-11-22" @default.
- W2986797487 creator A5002115637 @default.
- W2986797487 creator A5013920556 @default.
- W2986797487 creator A5016815495 @default.
- W2986797487 creator A5027487816 @default.
- W2986797487 creator A5035352293 @default.
- W2986797487 creator A5056508217 @default.
- W2986797487 creator A5057414041 @default.
- W2986797487 creator A5090741064 @default.
- W2986797487 date "2020-03-01" @default.
- W2986797487 modified "2023-10-18" @default.
- W2986797487 title "Improving brain age prediction models: incorporation of amyloid status in Alzheimer's disease" @default.
- W2986797487 cites W1987777001 @default.
- W2986797487 cites W1993571512 @default.
- W2986797487 cites W2040305148 @default.
- W2986797487 cites W2040775018 @default.
- W2986797487 cites W2075348467 @default.
- W2986797487 cites W2108103428 @default.
- W2986797487 cites W2129497119 @default.
- W2986797487 cites W2137229374 @default.
- W2986797487 cites W2147370235 @default.
- W2986797487 cites W2503987791 @default.
- W2986797487 cites W2552208519 @default.
- W2986797487 cites W2606346834 @default.
- W2986797487 cites W2766141193 @default.
- W2986797487 cites W2792578179 @default.
- W2986797487 cites W2809445583 @default.
- W2986797487 cites W2907829717 @default.
- W2986797487 cites W2951042025 @default.
- W2986797487 doi "https://doi.org/10.1016/j.neurobiolaging.2019.11.005" @default.
- W2986797487 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7064421" @default.
- W2986797487 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31843257" @default.
- W2986797487 hasPublicationYear "2020" @default.
- W2986797487 type Work @default.
- W2986797487 sameAs 2986797487 @default.
- W2986797487 citedByCount "32" @default.
- W2986797487 countsByYear W29867974872021 @default.
- W2986797487 countsByYear W29867974872022 @default.
- W2986797487 countsByYear W29867974872023 @default.
- W2986797487 crossrefType "journal-article" @default.
- W2986797487 hasAuthorship W2986797487A5002115637 @default.
- W2986797487 hasAuthorship W2986797487A5013920556 @default.
- W2986797487 hasAuthorship W2986797487A5016815495 @default.
- W2986797487 hasAuthorship W2986797487A5027487816 @default.
- W2986797487 hasAuthorship W2986797487A5035352293 @default.
- W2986797487 hasAuthorship W2986797487A5056508217 @default.
- W2986797487 hasAuthorship W2986797487A5057414041 @default.
- W2986797487 hasAuthorship W2986797487A5090741064 @default.
- W2986797487 hasBestOaLocation W29867974871 @default.
- W2986797487 hasConcept C126322002 @default.
- W2986797487 hasConcept C142724271 @default.
- W2986797487 hasConcept C15744967 @default.
- W2986797487 hasConcept C169760540 @default.
- W2986797487 hasConcept C2777633098 @default.
- W2986797487 hasConcept C2779134260 @default.
- W2986797487 hasConcept C502032728 @default.
- W2986797487 hasConcept C71924100 @default.
- W2986797487 hasConceptScore W2986797487C126322002 @default.
- W2986797487 hasConceptScore W2986797487C142724271 @default.
- W2986797487 hasConceptScore W2986797487C15744967 @default.
- W2986797487 hasConceptScore W2986797487C169760540 @default.
- W2986797487 hasConceptScore W2986797487C2777633098 @default.
- W2986797487 hasConceptScore W2986797487C2779134260 @default.
- W2986797487 hasConceptScore W2986797487C502032728 @default.
- W2986797487 hasConceptScore W2986797487C71924100 @default.
- W2986797487 hasFunder F4320337337 @default.
- W2986797487 hasFunder F4320337346 @default.
- W2986797487 hasLocation W29867974871 @default.
- W2986797487 hasLocation W29867974872 @default.
- W2986797487 hasOpenAccess W2986797487 @default.
- W2986797487 hasPrimaryLocation W29867974871 @default.
- W2986797487 hasRelatedWork W1517283793 @default.
- W2986797487 hasRelatedWork W1867806574 @default.
- W2986797487 hasRelatedWork W1990084059 @default.
- W2986797487 hasRelatedWork W2044788929 @default.
- W2986797487 hasRelatedWork W2065678033 @default.
- W2986797487 hasRelatedWork W2087409440 @default.
- W2986797487 hasRelatedWork W2094087479 @default.
- W2986797487 hasRelatedWork W2100610042 @default.
- W2986797487 hasRelatedWork W2809863685 @default.
- W2986797487 hasRelatedWork W4306247679 @default.
- W2986797487 hasVolume "87" @default.
- W2986797487 isParatext "false" @default.
- W2986797487 isRetracted "false" @default.
- W2986797487 magId "2986797487" @default.
- W2986797487 workType "article" @default.