Create README.md

README.md

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+---
+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 demonstrations
+
+## 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/).