  The development of diagnostic models for detecting and diagnosing pediatric
diseases in CXR scans is undertaken due to the lack of high-quality
physician-annotated datasets. To overcome this challenge, we introduce and
release PediCXR, a new pediatric CXR dataset of 9,125 studies retrospectively
collected from a major pediatric hospital in Vietnam between 2020 and 2021.
Each scan was manually annotated by a pediatric radiologist with more than ten
years of experience. The dataset was labeled for the presence of 36 critical
findings and 15 diseases. In particular, each abnormal finding was identified
via a rectangle bounding box on the image. To the best of our knowledge, this
is the first and largest pediatric CXR dataset containing lesion-level
annotations and image-level labels for the detection of multiple findings and
diseases. For algorithm development, the dataset was divided into a training
set of 7,728 and a test set of 1,397. To encourage new advances in pediatric
CXR interpretation using data-driven approaches, we provide a detailed
description of the PediCXR data sample and make the dataset publicly available
on https://physionet.org/content/pedicxr/1.0.0/
