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GIST 2.0: A Scalable Multi-trait Metric for Quantifying Population Representativeness of Individual Clinical Studies

The design of randomized controlled clinical studies can greatly benefit from iterative assessments of population representativeness of eligibility criteria. We propose a multi-trait metric - GIST 2.0 that can compute the a priori generalizability based on the population representativeness of a clin...

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Detalles Bibliográficos
Publicado en:J Biomed Inform
Autores principales: Sen, Anando, Chakrabarti, Shreya, Goldstein, Andrew, Wang, Shuang, Ryan, Patrick, Weng, Chunhua
Formato: Artigo
Lenguaje:Inglês
Publicado: 2016
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Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC5077682/
https://ncbi.nlm.nih.gov/pubmed/27600407
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jbi.2016.09.003
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