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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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Detalles Bibliográficos
Autores principales: Kury, Fabrício, Butler, Alex, Yuan, Chi, Fu, Li-heng, Sun, Yingcheng, Liu, Hao, Sim, Ida, Carini, Simona, Weng, Chunhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7452886/
https://www.ncbi.nlm.nih.gov/pubmed/32855408
http://dx.doi.org/10.1038/s41597-020-00620-0
Descripción
Sumario: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.