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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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Dades bibliogràfiques
Publicat a:J Biomed Inform
Autors principals: Sen, Anando, Chakrabarti, Shreya, Goldstein, Andrew, Wang, Shuang, Ryan, Patrick, Weng, Chunhua
Format: Artigo
Idioma:Inglês
Publicat: 2016
Matèries:
Accés en línia: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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