Cargando…
A computational method to quantitatively measure pediatric drug safety using electronic medical records
BACKGROUND: Drug safety in children is a major concern; however, there is still a lack of methods for quantitatively measuring, let alone to improving, drug safety in children under different clinical conditions. To assess pediatric drug safety under different clinical conditions, a computational me...
Autores principales: | Yu, Gang, Zeng, Xian, Ni, Shaoqing, Jia, Zheng, Chen, Weihong, Lu, Xudong, An, Jiye, Duan, Huilong, Shu, Qiang, Li, Haomin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6961323/ https://www.ncbi.nlm.nih.gov/pubmed/31937265 http://dx.doi.org/10.1186/s12874-020-0902-x |
Ejemplares similares
-
PedMap: a pediatric diseases map generated from clinical big data from Hangzhou, China
por: Li, Haomin, et al.
Publicado: (2019) -
Application of openEHR archetypes to automate data quality rules for electronic health records: a case study
por: Tian, Qi, et al.
Publicado: (2021) -
Explainable machine-learning predictions for complications after pediatric congenital heart surgery
por: Zeng, Xian, et al.
Publicado: (2021) -
Prediction of central venous catheter-associated deep venous thrombosis in pediatric critical care settings
por: Li, Haomin, et al.
Publicado: (2021) -
Risk factors for central venous catheter-associated deep venous thrombosis in pediatric critical care settings identified by fusion model
por: Li, Haomin, et al.
Publicado: (2022)