Deep learning for classification of pediatric chest radiographs by WHO's standardized methodology.

ABSTRACT:

Background

The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiveness studies in children. Automating the WHO methodology may support more widespread application of this endpoint.

Methods

We trained a deep learning model to classify pneumonia CXRs in children using the World Health Organization (WHO)'s standardized methodology. The model was pretrained on CheXpert, a dataset containing 224,316 adult CXRs, and fine-tuned on PERCH, a pediatric dataset containing 4,172 CXRs. The model was then tested on two pediatric CXR datasets released by WHO. We also compared the model's performance to that of radiologists and pediatricians.

Results

The average area under the receiver operating charact

SUBMITTER: Chen Y 

PROVIDER: S-EPMC8216551 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature