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task
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trial-approval-prediction-Phase1-test_x
Phase1
test_x
"{'Active Comparator Arm Number': {'NCT01852890': 0.0, 'NCT01136122': 1.0, 'NCT02133742': 0.0, 'NCT0(...TRUNCATED)
trial-approval-prediction-Phase1-test_y
Phase1
test_y
"{'outcome': {'NCT01852890': 1, 'NCT01136122': 0, 'NCT02133742': 1, 'NCT02121860': 1, 'NCT01143545':(...TRUNCATED)
trial-approval-prediction-Phase1-train_x
Phase1
train_x
"{'Active Comparator Arm Number': {'NCT00452582': 1.0, 'NCT04526912': 0.0, 'NCT03590860': 0.0, 'NCT0(...TRUNCATED)
trial-approval-prediction-Phase1-train_y
Phase1
train_y
"{'outcome': {'NCT00452582': 0, 'NCT04526912': 0, 'NCT03590860': 0, 'NCT01042704': 1, 'NCT02673736':(...TRUNCATED)
trial-approval-prediction-Phase2-test_x
Phase2
test_x
"{'Active Comparator Arm Number': {'NCT01436890': 0.0, 'NCT01215032': 0.0, 'NCT00529581': nan, 'NCT0(...TRUNCATED)
trial-approval-prediction-Phase2-test_y
Phase2
test_y
"{'outcome': {'NCT01436890': 1, 'NCT01215032': 0, 'NCT00529581': 0, 'NCT01366534': 0, 'NCT01767090':(...TRUNCATED)
trial-approval-prediction-Phase2-train_x
Phase2
train_x
"{'Active Comparator Arm Number': {'NCT01461993': 2.0, 'NCT00170677': 1.0, 'NCT03451006': 1.0, 'NCT0(...TRUNCATED)
trial-approval-prediction-Phase2-train_y
Phase2
train_y
"{'outcome': {'NCT01461993': 1, 'NCT00170677': 1, 'NCT03451006': 0, 'NCT02928393': 0, 'NCT04671901':(...TRUNCATED)
trial-approval-prediction-Phase3-test_x
Phase3
test_x
"{'Active Comparator Arm Number': {'NCT00295763': 0.0, 'NCT01810939': 1.0, 'NCT00363896': 0.0, 'NCT0(...TRUNCATED)
trial-approval-prediction-Phase3-test_y
Phase3
test_y
"{'outcome': {'NCT00295763': 1, 'NCT01810939': 1, 'NCT00363896': 1, 'NCT00617656': 0, 'NCT01594333':(...TRUNCATED)
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

Clinical Trial Dataset

This dataset contains data for multiple clinical trial prediction tasks. Each task includes multiple phases, with training and testing data provided in CSV format.

Dataset Structure

The dataset is structured as follows:

  • Tasks: Different clinical trial prediction tasks.
  • Phases: Different phases for each task (e.g., Phase1, Phase2).
  • Types: Training and testing data (e.g., train_x, train_y, test_x, test_y, train, test).

Each row in the dataset represents a file, with features or labels provided for prediction tasks.

Usage

To use this dataset, you can load it using the datasets library from Hugging Face.

Loading the Dataset

You can load the dataset as follows:

from datasets import load_dataset
import pandas as pd
import numpy as np

if __name__ == '__main__':
    data = {}
    dataset = load_dataset('ML2Healthcare/ClinicalTrialDataset')
    dataset = dataset['train'].to_dict()
    for task, phase, type_, table in zip(dataset['task'], dataset['phase'], dataset['type'], dataset['data']):
        table = pd.DataFrame.from_dict(eval(table, {'nan': np.nan}))
        table_name = f"{task}_{phase}_{type_}"
        data[table_name] = table
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