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Large-scale evidence generation and evaluation across a network of databases (LEGEND): assessing validity using hypertension as a case study.
Journal of the American Medical Informatics Association ( IF 6.4 ) Pub Date : 2020-09-10 , DOI: 10.1093/jamia/ocaa124 Martijn J Schuemie 1, 2 , Patrick B Ryan 1, 3 , Nicole Pratt 4 , RuiJun Chen 3, 5 , Seng Chan You 6 , Harlan M Krumholz 7 , David Madigan 8 , George Hripcsak 3, 9 , Marc A Suchard 2, 10
Journal of the American Medical Informatics Association ( IF 6.4 ) Pub Date : 2020-09-10 , DOI: 10.1093/jamia/ocaa124 Martijn J Schuemie 1, 2 , Patrick B Ryan 1, 3 , Nicole Pratt 4 , RuiJun Chen 3, 5 , Seng Chan You 6 , Harlan M Krumholz 7 , David Madigan 8 , George Hripcsak 3, 9 , Marc A Suchard 2, 10
Affiliation
To demonstrate the application of the Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND) principles described in our companion article to hypertension treatments and assess internal and external validity of the generated evidence.
中文翻译:
跨数据库网络 (LEGEND) 的大规模证据生成和评估:使用高血压作为案例研究评估有效性。
展示我们的配套文章中描述的跨数据库网络 (LEGEND) 原则的大规模证据生成和评估在高血压治疗中的应用,并评估所生成证据的内部和外部有效性。
更新日期:2020-09-10
中文翻译:
跨数据库网络 (LEGEND) 的大规模证据生成和评估:使用高血压作为案例研究评估有效性。
展示我们的配套文章中描述的跨数据库网络 (LEGEND) 原则的大规模证据生成和评估在高血压治疗中的应用,并评估所生成证据的内部和外部有效性。