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task
stringlengths 28
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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) |
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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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