Artificial intelligence-assisted automated heart failure detection and classification from electronic health records.

ABSTRACT:

Aims

Electronic health records (EHR) linked to Digital Imaging and Communications in Medicine (DICOM), biological specimens, and deep learning (DL) algorithms could potentially improve patient care through automated case detection and surveillance. We hypothesized that by applying keyword searches to routinely stored EHR, in conjunction with AI-powered automated reading of DICOM echocardiography images and analysing biomarkers from routinely stored plasma samples, we were able to identify heart failure (HF) patients.

Methods and results

We used EHR data between 1993 and 2021 from Tayside and Fife (~20% of the Scottish population). We implemented a keyword search strategy complemented by filtering based on International Classification of Diseases (ICD) codes and prescription

SUBMITTER: Oo MM 

PROVIDER: S-EPMC11424299 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature