Artificial intelligence automation of echocardiographic measurements.

ABSTRACT:

Background

Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time, however manual assessment is time-consuming and can be imprecise. Artificial intelligence (AI) has the potential to reduce clinician burden by automating the time-intensive task of comprehensive measurement of echocardiographic parameters.

Methods

We developed and validated open-sourced deep learning semantic segmentation models for the automated measurement of 18 anatomic and Doppler measurements in echocardiography. The outputs of segmentation models were compared to sonographer measurements from two institutions to access accuracy and precision.

Results

We utilized 877,983 echocardiographic measurements from 155,21

SUBMITTER: Sahashi Y 

PROVIDER: S-EPMC11957091 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature