README.md

metadata

task_categories:
  - image-classification
language:
  - en
tags:
  - medical
pretty_name: chest-xray
size_categories:
  - 1K<n<10K
license: cc

chest-xray

Overview

The chest-xray dataset can be employed as the training and test sets for computer vision tasks like pneumonia classification.

Dataset Details

This data originally came from Chest X-Ray Images (Pneumonia)

The original dataset contains : The dataset is organized into 3 folders (train, test, val) and contains subfolders for each image category (Pneumonia/Normal). There are 5,856 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal).

@article{kermany2018identifying,
  title={Identifying medical diagnoses and treatable diseases by image-based deep learning},
  author={Kermany, Daniel S and Goldbaum, Michael and Cai, Wenjia and Valentim, Carolina CS and Liang, Huiying and Baxter, Sally L and McKeown, Alex and Yang, Ge and Wu, Xiaokang and Yan, Fangbing and others},
  journal={cell},
  volume={172},
  number={5},
  pages={1122--1131},
  year={2018},
  publisher={Elsevier}
}

• Dataset Name: chest-xray
• Language: English
• Total Size: 5,856 images

Contents

The dataset consists of Chest X-ray images (anterior-posterior), and 2 class labels:

• "0" normal(27%)
• "1" pneumonia(73%)

How to use

from datasets import load_dataset

dataset = load_dataset("AiresPucrs/chest-xray", split='train')

License

The dataset is licensed under the Creative Commons License CC0 4.0 International.