CTO: Clinical Trial Outcome Prediction Benchmark

A dataset for predicting clinical trial outcomes in drug development, presented in the paper 'Automatically Labeling Clinical Trial Outcomes: A Large-Scale Benchmark for Drug Development'. It includes a manually annotated subset called 'human_labels'. The dataset was created by author chufangao and was last updated on 2025-10-27.

Use Cases

• Predicting drug trial success or failure based on annotated clinical trial data.
• Training models for automated labeling of clinical trial outcomes as described in the associated paper.
• Benchmarking machine learning algorithms on structured medical data for drug development.

Strengths

• Includes a manually annotated subset ('human_labels') for supervised learning.
• Associated with a published research paper and code repository, providing methodological context.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.

Provenance

Source

huggingface

Collection Method

Likely compiled from clinical trial records, with manual annotation for a subset.

Freshness

Last updated 2025-10-27 03:41:15; freshness should be verified.