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Chest X-ray Images
2D Classification
Aesthetics
|...
许可协议: CC-BY-SA 4.0

Overview

Context

Pneumonia is an infection that inflames the air sacs in one or both lungs. It kills more children younger than 5 years old each year than any other infectious disease, such as HIV infection, malaria, or tuberculosis. Diagnosis is often based on symptoms and physical examination. Chest X-rays may help confirm the diagnosis.

Content

This dataset contains 5,856 validated Chest X-Ray images. The images are split into a training set and a testing set of independent patients. Images are labeled as (disease:NORMAL/BACTERIA/VIRUS)-(randomized patient ID)-(image number of a patient). For details of the data collection and description, see the referenced paper below.

According to the paper, the images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou.

A previous version (v2) of this dataset is available here: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia. Note that the files names are irregular in v2, but they are fixed in the new version (v3).

Inspiration

This data will be useful for developing/training/testing classification models with convolutional neural networks.

Acknowledgements

This dataset is taken from https://data.mendeley.com/datasets/rscbjbr9sj/3.

Licence: CC BY 4.0

Reference: https://www.cell.com/cell/fulltext/S0092-8674(18)30154-5

数据概要
数据格式
image,
数据量
5.856K
文件大小
149.95MB
发布方
Chebu
| 数据量 5.856K | 大小 149.95MB
Chest X-ray Images
2D Classification
Aesthetics
许可协议: CC-BY-SA 4.0

Overview

Context

Pneumonia is an infection that inflames the air sacs in one or both lungs. It kills more children younger than 5 years old each year than any other infectious disease, such as HIV infection, malaria, or tuberculosis. Diagnosis is often based on symptoms and physical examination. Chest X-rays may help confirm the diagnosis.

Content

This dataset contains 5,856 validated Chest X-Ray images. The images are split into a training set and a testing set of independent patients. Images are labeled as (disease:NORMAL/BACTERIA/VIRUS)-(randomized patient ID)-(image number of a patient). For details of the data collection and description, see the referenced paper below.

According to the paper, the images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou.

A previous version (v2) of this dataset is available here: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia. Note that the files names are irregular in v2, but they are fixed in the new version (v3).

Inspiration

This data will be useful for developing/training/testing classification models with convolutional neural networks.

Acknowledgements

This dataset is taken from https://data.mendeley.com/datasets/rscbjbr9sj/3.

Licence: CC BY 4.0

Reference: https://www.cell.com/cell/fulltext/S0092-8674(18)30154-5

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