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Blaisure, J. C., & Ceusters, W. M. (2018). Improving the ‘Fitness for Purpose’ of Common Data Models through Realism Based Ontology. AMIA Annual Symposium Proceedings, 2017, 440–447.
Boland, M. R., Parhi, P., Li, L., Miotto, R., Carroll, R., Iqbal, U., … Tatonetti, N. P. (2018). Uncovering exposures responsible for birth season – disease effects: a global study. Journal of the American Medical Informatics Association, 25(3), 275–288. https://doi.org/10.1093/jamia/ocx105
Butler, A., Wei, W., Yuan, C., Kang, T., Si, Y., & Weng, C. (2018). The Data Gap in the EHR for Clinical Research Eligibility Screening. AMIA Summits on Translational Science Proceedings, 2017, 320–329.
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Natsiavas, P., Boyce, R. D., Jaulent, M.-C., & Koutkias, V. (2018). OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies. Frontiers in Pharmacology, 9. https://doi.org/10.3389/fphar.2018.00609
Nestsiarovich, A., Mazurie, A. J., Hurwitz, N. G., Kerner, B., Nelson, S. J., Crisanti, A. S., … Lambert, C. G. (2018). Comprehensive comparison of monotherapies for psychiatric hospitalization risk in bipolar disorders. Bipolar Disorders, 20(8), 761–771. https://doi.org/10.1111/bdi.12665
Pacaci, A., Gonul, S., Sinaci, A. A., Yuksel, M., & Laleci Erturkmen, G. B. (2018). A Semantic Transformation Methodology for the Secondary Use of Observational Healthcare Data in Postmarketing Safety Studies. Frontiers in Pharmacology, 9. https://doi.org/10.3389/fphar.2018.00435
Patadia, V. K., Schuemie, M. J., Coloma, P. M., Herings, R., van der Lei, J., Sturkenboom, M., & Trifirò, G. (2018). Can Electronic Health Records Databases Complement Spontaneous Reporting System Databases? A Historical-Reconstruction of the Association of Rofecoxib and Acute Myocardial Infarction. Frontiers in Pharmacology, 9, 594. https://doi.org/10.3389/fphar.2018.00594
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Reps, J. M., Schuemie, M. J., Suchard, M. A., Ryan, P. B., & Rijnbeek, P. R. (2018). Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. Journal of the American Medical Informatics Association: JAMIA, 25(8), 969–975. https://doi.org/10.1093/jamia/ocy032
Ryan, P. B., Buse, J. B., Schuemie, M. J., DeFalco, F., Yuan, Z., Stang, P. E., … Rosenthal, N. (2018). Comparative effectiveness of canagliflozin, SGLT2 inhibitors and non-SGLT2 inhibitors on the risk of hospitalization for heart failure and amputation in patients with type 2 diabetes mellitus: A real-world meta-analysis of 4 observational databases (OBSERVE-4D). Diabetes, Obesity & Metabolism, 20(11), 2585–2597. https://doi.org/10.1111/dom.13424
Schuemie, M. J., Hripcsak, G., Ryan, P. B., Madigan, D., & Suchard, M. A. (2018). Empirical confidence interval calibration for population-level effect estimation studies in observational healthcare data. Proceedings of the National Academy of Sciences of the United States of America, 115(11), 2571–2577. https://doi.org/10.1073/pnas.1708282114
Tian, Y., Schuemie, M. J., & Suchard, M. A. (2018). Evaluating large-scale propensity score performance through real-world and synthetic data experiments. International Journal of Epidemiology, 47(6), 2005–2014. https://doi.org/10.1093/ije/dyy120
Vilar, S., Friedman, C., & Hripcsak, G. (2018). Detection of drug-drug interactions through data mining studies using clinical sources, scientific literature and social media. Briefings in Bioinformatics, 19(5), 863–877. https://doi.org/10.1093/bib/bbx010
Yang, Y., Zhou, X., Gao, S., Lin, H., Xie, Y., Feng, Y., … Zhan, S. (2018). Evaluation of Electronic Healthcare Databases for Post-Marketing Drug Safety Surveillance and Pharmacoepidemiology in China. Drug Safety, 41(1), 125–137. https://doi.org/10.1007/s40264-017-0589-z