Datasets:
Update README.md
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README.md
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task_categories:
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- image-classification
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- feature-extraction
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---
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task_categories:
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- image-classification
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- feature-extraction
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---
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## Dataset Structure
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This dataset contains vision data for chest X-ray pathology identification.
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### Data Fields
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- **image**: The PIL image of the chest X-ray. These images are size (224,224) by default.
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- **pathols**: A binary-valued (14)-shaped array that indicates whether each of the 14 pathologies is present.
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- **structs**: A binary-valued array of shapes (14,224,224) that gives the segmentation for each of the 14 anatomical structures.
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The 14 pathologies are:
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0. Atelectasis
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1. Cardiomegaly
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2. Consolidation
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3. Edema
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4. Effusion
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5. Emphysema
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6. Fibrosis
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7. Hernia
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8. Infiltration
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9. Mass
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10. Nodule
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11. Pleural Thickening
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12. Pneumonia
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13. Pneumothorax
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The 14 anatomical structures are:
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0. Left Clavicle
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1. Right Clavicle
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2. Left Scapula
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3. Right Scapula
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4. Left Lung
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5. Right Lung
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6. Left Hilus Pulmonis
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7. Right Hilus Pulmonis
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8. Heart
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9. Aorta
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10. Facies Diaphragmatica
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11. Mediastinum
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12. Weasand
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13. Spine
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### Data Splits
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- **train**: 23094 samples
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- **test**: 5774 samples
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## Usage
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```
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from datasets import load_dataset
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train_dataset = load_dataset("BrachioLab/chestx", split="train")
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test_dataset = load_dataset("BrachioLab/chestx", split="test")
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```
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