4.7 Article Data Paper

BRAX, Brazilian labeled chest x-ray dataset

Journal

SCIENTIFIC DATA
Volume 9, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41597-022-01608-8

Keywords

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Funding

  1. MIT-Brazil TVML Seed Fund award (project Developing a Publicly Accessible Brazilian Dataset of Chest X-Rays)
  2. National Institute of Health through the NIBIB R01 grant [EB017205]
  3. National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH [R01EB030362]

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This paper describes a automatically labeled Brazilian chest x-ray dataset, BRAX, designed to assist researchers in validating machine learning models. The dataset includes a large number of chest radiography studies from a Brazilian general hospital, totaling 40,967 images.
Chest radiographs allow for the meticulous examination of a patient's chest but demands specialized training for proper interpretation. Automated analysis of medical imaging has become increasingly accessible with the advent of machine learning (ML) algorithms. Large labeled datasets are key elements for training and validation of these ML solutions. In this paper we describe the Brazilian labeled chest x-ray dataset, BRAX: an automatically labeled dataset designed to assist researchers in the validation of ML models. The dataset contains 24,959 chest radiography studies from patients presenting to a large general Brazilian hospital. A total of 40,967 images are available in the BRAX dataset. All images have been verified by trained radiologists and de-identified to protect patient privacy. Fourteen labels were derived from free-text radiology reports written in Brazilian Portuguese using Natural Language Processing.

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