Self-Organizing Maps to Multidimensionally Characterize Physical Profiles in Older Adults.

ABSTRACT: The aim of this study is to automatically analyze, characterize and classify physical performance and body composition data of a cohort of Mexican community-dwelling older adults. Self-organizing maps (SOM) were used to identify similar profiles in 562 older adults living in Mexico City that participated in this study. Data regarding demographics, geriatric syndromes, comorbidities, physical performance, and body composition were obtained. The sample was divided by sex, and the multidimensional analysis included age, gait speed over height, grip strength over body mass index, one-legged stance, lean appendicular mass percentage, and fat percentage. Using the SOM neural network, seven profile types for older men and women were identified. This analysis provided maps depicting a set of clust

SUBMITTER: Parra-Rodriguez L 

PROVIDER: S-EPMC9565208 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature