Chia, a large annotated corpus of clinical trial eligibility criteria

We present Chia, a novel, large annotated corpus of patient eligibility criteria extracted from 1,000 interventional, Phase IV clinical trials registered in ClinicalTrials.gov. This dataset includes 12,409 annotated eligibility criteria, represented by 41,487 distinctive entities of 15 entity types...

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Bibliographic Details
Published inScientific data Vol. 7; no. 1; p. 281
Main Authors Kury, Fabrício, Butler, Alex, Yuan, Chi, Fu, Li-heng, Sun, Yingcheng, Liu, Hao, Sim, Ida, Carini, Simona, Weng, Chunhua
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 27.08.2020
Nature Publishing Group
Subjects
692/308/2779/109
Clinical trials
Clinical Trials, Phase IV as Topic
Computer applications
Data Descriptor
Digital curation
Humanities and Social Sciences
Humans
Learning algorithms
Machine learning
multidisciplinary
Science
Science (multidisciplinary)
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Summary:We present Chia, a novel, large annotated corpus of patient eligibility criteria extracted from 1,000 interventional, Phase IV clinical trials registered in ClinicalTrials.gov. This dataset includes 12,409 annotated eligibility criteria, represented by 41,487 distinctive entities of 15 entity types and 25,017 relationships of 12 relationship types. Each criterion is represented as a directed acyclic graph, which can be easily transformed into Boolean logic to form a database query. Chia can serve as a shared benchmark to develop and test future machine learning, rule-based, or hybrid methods for information extraction from free-text clinical trial eligibility criteria. Measurement(s) Clinical Trial Eligibility Criteria • Analytical Procedure Accuracy Technology Type(s) digital curation • computational modeling technique Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12765602
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-020-00620-0