GIST 2.0: A scalable multi-trait metric for quantifying population representativeness of individual clinical studies-Reference-Cited by-同舟云学术

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GIST 2.0: A scalable multi-trait metric for quantifying population representativeness of individual clinical studies

Published:2016-10 Issue: Volume:63 Page:325-336
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Sen Anando,Chakrabarti Shreya,Goldstein Andrew,Wang Shuang,Ryan Patrick B.,Weng Chunhua

Funder

National Library of Medicine

National Center for Advancing Translational Sciences

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference39 articles.

1. Evaluating the relevance, generalization, and applicability of research issues in external validation and translation methodology;Green;Eval. Health Professions,2006

2. Generalizability the trees, the forest, and the low-hanging fruit;Kukull;Neurology,2012

3. What researchers mean by generalizability;Dubey;At Work,2006

4. Formal representation of eligibility criteria: a literature review;Weng;J. Biomed. Inform.,2010

5. The age gap between patients in clinical studies and in the general population: a pitfall for dementia research;Schoenmaker;Lancet Neurol.,2004

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