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# Clinical Trial Dataset |
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This dataset contains data for multiple clinical trial prediction tasks. Each task includes multiple phases, with training and testing data provided in CSV format. |
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## Dataset Structure |
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The dataset is structured as follows: |
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- **Tasks**: Different clinical trial prediction tasks. |
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- **Phases**: Different phases for each task (e.g., Phase1, Phase2). |
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- **Types**: Training and testing data (e.g., train_x, train_y, test_x, test_y, train, test). |
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Each row in the dataset represents a file, with features or labels provided for prediction tasks. |
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## Usage |
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To use this dataset, you can load it using the `datasets` library from Hugging Face. |
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### Loading the Dataset |
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You can load the dataset as follows: |
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```python |
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from datasets import load_dataset |
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import pandas as pd |
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import numpy as np |
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if __name__ == '__main__': |
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data = {} |
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dataset = load_dataset('ML2Healthcare/ClinicalTrialDataset') |
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dataset = dataset['train'].to_dict() |
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for task, phase, type_, table in zip(dataset['task'], dataset['phase'], dataset['type'], dataset['data']): |
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table = pd.DataFrame.from_dict(eval(table, {'nan': np.nan})) |
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table_name = f"{task}_{phase}_{type_}" |
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data[table_name] = table |