Dataset
clinical-trials-trec-topics
The clinical-trials-trec-topics dataset is a small tabular collection of clinical-trial topic records distributed in Parquet format on the Hugging Face Hub. It appears to be derived from TREC clinical-trial retrieval topics, with rows partitioned by year.
Data preview
Dataset card
What this dataset contains
The dataset holds 165 rows split across the years 2021, 2022 and 2023, each row representing a single clinical-trial topic used for information-retrieval benchmarking. According to the publisher metadata it is a tabular and text resource with under one thousand records, indicating it is a curated topic set rather than a full corpus of trial documents.
Structure and fields
Three columns are defined: topic_id as an int64 value, year as an int64 value, and patient_description as a string value. The dataset ships in Parquet and is loadable through the datasets, pandas, polars and mlcroissant libraries. Sample rows in the publisher's preview are masked, so the exact content of patient_description cannot be inspected from the listing.
How analysts use it
Given its origin as TREC topic data, the natural use case is constructing or evaluating clinical-trial search and retrieval models, where each topic_id is paired with a free-text patient_description that drives query formulation. The year column allows researchers to slice topics by cohort vintage when comparing system behaviour over time. Investment-oriented use cases are not directly suggested by the schema or metadata, and the dataset's small size and academic framing limit its role as an alternative-data signal.
Documentation & references 1
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