Ontology highlight
ABSTRACT: Importance
Increased ability to quantify anatomical phenotypes across multiple organs provides the opportunity to assess their cumulative ability to identify individuals at greatest susceptibility for adverse outcomes.Objective
To apply unsupervised machine learning to define the distribution and prognostic importance of computed tomography-based multiorgan phenotypes associated with adverse health outcomes.Design, setting, and participants
This asymptomatic community-based cohort study included 2924 Framingham Heart Study participants between July 2002 and April 2005 undergoing computed tomographic imaging of the chest and abdomen. Participants are from the offspring and third-generation cohorts.Exposures
Eleven computed tomography-based measures of valvula
SUBMITTER: Shah RV
PROVIDER: S-EPMC5710362 | biostudies-literature | 2017 Nov
REPOSITORIES: biostudies-literature