Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease. The New England journal of medicine. 2016 Mar 24;374(374). 1134-44. PMID: 26934567 [PubMed]
Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC).
Hoffman JM, Dunnenberger HM, Kevin Hicks J, Caudle KE, Whirl Carrillo M, Freimuth RR, Williams MS, Klein TE, Peterson JF. Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC). Journal of the American Medical Informatics Association : JAMIA. 2016 Mar 28. PMID: 27026620 [PubMed]
Gamazon ER, Wheeler HE, Shah KP, Mozaffari SV, Aquino-Michaels K, Carroll RJ, Eyler AE, Denny JC, Nicolae DL, Cox NJ, Im HK. A gene-based association method for mapping traits using reference transcriptome data. Nature genetics. 2015 Sep;47(47). 1091-8. PMID: 26258848 [PubMed] PMCID: PMC4552594 NIHMSID: NIHMS706045.
Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype.
Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance.
Wei WQ, Teixeira PL, Mo H, Cronin RM, Warner JL, Denny JC. Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance. Journal of the American Medical Informatics Association : JAMIA. 2015 Sep 2. PMID: 26338219 [PubMed]
To evaluate the phenotyping performance of three major electronic health record (EHR) components: International Classification of Disease (ICD) diagnosis codes, primary notes, and specific medications.
Mo H, Thompson WK, Rasmussen LV, Pacheco JA, Jiang G, Kiefer R, Zhu Q, Xu J, Montague E, Carrell DS, Lingren T, Mentch FD, Ni Y, Wehbe FH, Peissig PL, Tromp G, Larson EB, Chute CG, Pathak J, Denny JC, Speltz P, Kho AN, Jarvik GP, Bejan CA, Williams MS, Borthwick K, Kitchner TE, Roden DM, Harris PA. Desiderata for computable representations of electronic health records-driven phenotype algorithms. Journal of the American Medical Informatics Association : JAMIA. 2015 Nov;22(22). 1220-30. PMID: 26342218 [PubMed] PMCID: PMC4639716
A prognostic model based on readily available clinical data enriched a preemptive pharmacogenetic testing program.
Schildcrout JS, Shi Y, Danciu I, Bowton E, Field JR, Pulley JM, Basford M, Gregg W, Cowan J, Harrell FE, Roden DM, Peterson JF, Denny JC. A prognostic model based on readily available clinical data enriched a preemptive pharmacogenetic testing program. Journal of clinical epidemiology. 2015 Nov 25. PMID: 26628336 [PubMed]
Roden DM, Denny JC. Integrating electronic health record genotype and phenotype datasets to transform patient care. Clinical pharmacology and therapeutics. 2015 Dec 14. PMID: 26667791 [PubMed]
The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 mandates the development and implementation of electronic health record (EHR) systems across the country.
Denny JC, Smithers JD, Miller RA, Spickard A. "Understanding" medical school curriculum content using KnowledgeMap. Journal of the American Medical Informatics Association : JAMIA. 10(10). 351-62. PMID: 12668688 [PubMed] PMCID: PMC181986
To describe the development and evaluation of computational tools to identify concepts within medical curricular documents, using information derived from the National Library of Medicine's Unified Medical Language System (UMLS). The long-term goal of the KnowledgeMap (KM) project is to provide faculty and students with an improved ability to develop, review, and integrate components of the medical school curriculum.
Denny JC, Irani PR, Wehbe FH, Smithers JD, Spickard A. The KnowledgeMap project: development of a concept-based medical school curriculum database. AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 195-9. PMID: 14728161 [PubMed] PMCID: PMC1480333
We developed the KnowledgeMap (KM) system as an online, concept-based database of medical school curriculum documents. It uses the KM concept indexer to map full-text documents and match search queries to concepts in the Unified Medical Language System (UMLS). In this paper, we describe the design of KM and report the first seven months of its implementation into a medical school. Despite being emphasized in only two first year courses and one fourth year course, students from all four classes used KM to search and browse documents.
Formative evaluation to guide early deployment of an online content management tool for medical curriculum.
Wehbe FH, Armstrong BK, Peachey MR, Denny JC, Spickard A. Formative evaluation to guide early deployment of an online content management tool for medical curriculum. AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 1049 p. PMID: 14728552 [PubMed] PMCID: PMC1479992
KM is a Web-accessible, comprehensive database that organizes course materials (at the level of full lectures, not just outlines or syllabi) from the Vanderbilt School of Medicine curriculum. KM uses natural language processing techniques to analyze educational documents for biomedical concepts. Lecture handouts and Microsoft PowerPoint presentations are indexed and available online for students, faculty and administrators to search for individual or interrelated concepts across the medical school curriculum.