language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
- image-to-image
tags:
- medical
- code
- biology
dataset_info:
features:
- name: image
dtype: image
- name: type
dtype: string
splits:
- name: train
num_bytes: 325782340
num_examples: 97
download_size: 313593688
dataset_size: 325782340
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Chest X-ray
The dataset consists of a collection of chest X-ray images in .jpg and .dcm formats. The images are organized into folders based on different medical conditions related to the chest. Each folder contains images depicting specific chest abnormalities.
Types of diseases and conditions in the dataset:
Abscess, Ards, Atelectasis, Atherosclerosis of the aorta, Cardiomegaly, Emphysema, Fracture, Hydropneumothorax, Hydrothorax, Pneumonia, Pneumosclerosis, Post inflammatory changes, Post traumatic ribs deformation, Sarcoidosis, Scoliosis, Tuberculosis and Venous congestion
The dataset is valuable for research in neurology, radiology, and oncology. It allows the development and evaluation of computer-based algorithms, machine learning models, and deep learning techniques for automated detection, diagnosis, and classification of these conditions.
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Content
The folder "files" includes 17 folders:
- corresponding to name of the disease/condition and including x-rays of people with this disease/condition (abscess, ards, atelectasis etc.)
- including x-rays in 2 different formats: .jpg and .dcm.
File with the extension .csv includes the following information for each media file:
- dcm: link to access the .dcm file,
- jpg: link to access the .jpg file,
- type: name of the disease or condition on the x-ray
Medical data might be collected in accordance with your requirements.
TrainingData provides high-quality data annotation tailored to your needs
More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets
TrainingData's GitHub: https://github.com/trainingdata-pro