Chia, a large annotated corpus of clinical trial eligibility criteria

Authors

Fabrício Kury, Columbia University
Alex Butler, Columbia University
Chi Yuan, Columbia University
Li heng Fu, Columbia University
Yingcheng Sun, Columbia University
Hao Liu, Columbia University
Ida Sim, University of California, San Francisco
Simona Carini, University of California, San Francisco
Chunhua Weng, Columbia University

Document Type

Syllabus

Publication Date

12-1-2020

Abstract

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.

Identifier

85089979753 (Scopus)

Publication Title

Scientific Data

External Full Text Location

https://doi.org/10.1038/s41597-020-00620-0

e-ISSN

20524463

PubMed ID

32855408

Issue

1

Volume

7

Grant

R01LM009886-10

Fund Ref

U.S. National Library of Medicine

Recommended Citation

Kury, Fabrício; Butler, Alex; Yuan, Chi; Fu, Li heng; Sun, Yingcheng; Liu, Hao; Sim, Ida; Carini, Simona; and Weng, Chunhua, "Chia, a large annotated corpus of clinical trial eligibility criteria" (2020). Faculty Publications. 4789.
https://digitalcommons.njit.edu/fac_pubs/4789