References
- Atlas. San Franciso: GitHub, 2019. Accessed 2019 Apr 2. Available from: https://github.com/OHDSI/Atlas.
- Reps JM, Schuemie MJ, Suchard MA, Ryan PB, Rijnbeek PR. Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. J Am Med Inform Assoc 2018;25:969-975. https://doi.org/10.1093/jamia/ocy032
- Banda JM, Halpern Y, Sontag D, Shah NH. Electronic phenotyping with APHRODITE and the Observational Health Sciences and Informatics (OHDSI) data network. AMIA Jt Summits Transl Sci Proc 2017;2017:48-57.
- Hripcsak G, Ryan PB, Duke JD, Shah NH, Park RW, Huser V, et al. Characterizing treatment pathways at scale using the OHDSI network. Proc Natl Acad Sci U S A 2016;113:7329-7336. https://doi.org/10.1073/pnas.1510502113
- Duke JD, Ryan PB, Suchard MA, Hripcsak G, Jin P, Reich C, et al. Risk of angioedema associated with levetiracetam compared with phenytoin: findings of the observational health data sciences and informatics research network. Epilepsia 2017;58:e101-e106. https://doi.org/10.1111/epi.13828
- Vashisht R, Jung K, Schuler A, Banda JM, Park RW, Jin S, et al. Association of hemoglobin A1c levels with use of sulfonylureas, dipeptidyl peptidase 4 inhibitors, and thiazolidinediones in patients with type 2 diabetes treated with metformin: analysis from the observational health data sciences and informatics initiative. JAMA Netw Open 2018;1:e181755. https://doi.org/10.1001/jamanetworkopen.2018.1755
- Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res 2004;32:D267-D270. https://doi.org/10.1093/nar/gkh061
- Callahan A, Cruz-Toledo J, Ansell P, Dumontier M. Bio2RDF release 2: improved coverage, interoperability and provenance of life science linked data. In: The Semantic Web: Semantics and Big Data (Cimiano P, Corcho O, Presutti V, Hollink L, Rodolph S, eds.), 2013 May 26-30, Montpellier, France. Berlin: Springer, 2013. pp. 200-212.
- Salvadores M, Alexander PR, Musen MA, Noy NF. BioPortal as a dataset of linked biomedical ontologies and terminologies in RDF. Semant Web 2013;4:277-284. https://doi.org/10.3233/SW-2012-0086
- OHDSIananke. San Franciso: GitHub, 2019. Accessed 2019 Apr 2. Available from: https://github.com/thepanacealab/OHDSIananke.
- Leroux H, Lefort L. Semantic enrichment of longitudinal clinical study data using the CDISC standards and the semantic statistics vocabularies. J Biomed Semantics 2015;6:16. https://doi.org/10.1186/s13326-015-0012-6
- Blair DR, Wang K, Nestorov S, Evans JA, Rzhetsky A. Quantifying the impact and extent of undocumented biomedical synonymy. PLoS Comput Biol 2014;10:e1003799. https://doi.org/10.1371/journal.pcbi.1003799
- Robinson PN, Kohler S, Bauer S, Seelow D, Horn D, Mundlos S. The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet 2008;83:610-615. https://doi.org/10.1016/j.ajhg.2008.09.017
- Henderson J, Bridges R, Ho JC, Wallace BC, Ghosh J. PheKnow-Cloud: a tool for evaluating high-throughput phenotype candidates using online medical literature. AMIA Jt Summits Transl Sci Proc 2017;2017:149-157.
- Ling Y, An Y, Liu M, Hasan SA, Fan Y, Hu X. Integrating extra knowledge into word embedding models for biomedical NLP tasks. In: 2017 International Joint Conference on Neural Networks (IJCNN), 2017 May 14-19, Anchorage, AK, USA. Hoffman Estates: International Joint Conference on Neural Networks, 2017. pp. 968-975.
- Dubois S, Romano N, Kale DC, Shah N, Jung K. Effective representations of clinical notes. Ithaca: arXiv, Cornell University, 2017. Accessed 2019 Apr 2. Available from: http://arxiv.org/abs/1705.07025.