Datasets › CHIP-CTC

CHIP-CTC

archive 2025-07-28

CHIP Clinical Trial Classification, a dataset aimed at classifying clinical trials eligibility criteria, which are fundamental guidelines of clinical trials defined to identify whether a subject meets a clinical trial or not, is used for the CHIP-CTC task. All text data are collected from the website of the Chinese Clinical Trial Registry (ChiCTR) , and a total of 44 categories are defined. The task is like text classification; although it is not a new task, studies and corpus for the Chinese clinical trial criterion are still limited, and we hope to promote future researches for social benefits.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Sentence Classification CHIP-CTC RoBERTa-large Macro F1 70.9 CBLUE: A Chinese Biomedical Language Understanding... cbluebenchmark/cblue +1 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 1. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark 2 1 15 Jun 2021 ran 4 of 16 samples (12 unverified)

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • CHIP-CTC

1 variant name, as the archive lists them.

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