Deep Phenotyping of Obesity: Electronic Health Record-Based Temporal Modeling Study.

ABSTRACT: Obesity affects approximately 40% of adults and 15%-20% of children and adolescents in the United States, and poses significant economic and psychosocial burdens. Currently, patient responses to any single antiobesity medication (AOM) vary significantly, making obesity deep phenotyping and associated precision medicine important targets of investigation. This study aimed to evaluate the potential of electronic health records (EHR) as a primary data source for obesity deep phenotyping. We conducted an in-depth analysis of the data elements and quality available from obesity patients prior to pharmacotherapy and applied a multimodal longitudinal deep autoencoder to investigate the feasibility, data requirements, clustering patterns, and challenges associated with EHR-based obesity deep pheno

SUBMITTER: Ruan X 

PROVIDER: S-EPMC12373304 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature