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.