Artificial intelligence approaches for phenotyping heart failure in U.S. Veterans Health Administration electronic health record.

ABSTRACT:

Aims

Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes. However, most HF patients are not hospitalized, and manual review of big electronic health record (EHR) data is not practical. The US Department of Veterans Affairs (VA) has the largest integrated healthcare system in the nation, and an estimated 1.5 million patients have ICD codes for HF (HF ICD-code universe) in their VA EHR. The objective of our study was to develop artificial intelligence (AI) models to phenotype HF in these patients.

Methods and results

The model development cohort (n = 20 000: training, 16 000; validation 2

SUBMITTER: Shao Y 

PROVIDER: S-EPMC11424308 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature