---
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)](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-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).


```latex
@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

```python
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](https://creativecommons.org/licenses/by/4.0/).