Differential diagnosis of congenital ventricular septal defect and atrial septal defect in children using deep learning-based analysis of chest radiographs.

ABSTRACT:

Background

Children with atrial septal defect (ASD) and ventricular septal defect (VSD) are frequently examined for respiratory symptoms, even when the underlying disease is not found. Chest radiographs often serve as the primary imaging modality. It is crucial to differentiate between ASD and VSD due to their distinct treatment.

Purpose

To assess whether deep learning analysis of chest radiographs can more effectively differentiate between ASD and VSD in children.

Methods

In this retrospective study, chest radiographs and corresponding radiology reports from 1,194 patients were analyzed. The cases were categorized into a training set and a validation set, comprising 480 cases of ASD and 480 cases of VSD, and a test set with 115 cases of ASD and 119 cases of VSD. Four

SUBMITTER: Jia H 

PROVIDER: S-EPMC11476512 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature