Denny, Joshua C.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

the RACI consortium, Okada, Y., the GARNET consortium, Wu, D., Trynka, G., Raj, T., Terao, C., Ikari, K., Kochi, Y., Ohmura, K., et al. (2014) · Nature

Rheumatoid Arthritis Research and TherapiesGenetic Associations and Epidemiology

Cited by 2,310

A genomic mutational constraint map using variation in 76,156 human genomes

Chen, S., Francioli, L. C., Goodrich, J. K., Collins, R. L., Kanai, M., Wang, Q., Alföldi, J., Watts, N. A., Vittal, C., Gauthier, L. D., et al. (2024) · Nature

Genomics and Rare DiseasesGenetic Associations and Epidemiology

Cited by 1,727

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations

Denny, J. C., Ritchie, M. D., Basford, M. A., Pulley, J. M., Bastarache, L., Brown-Gentry, K., Wang, D., Masys, D. R., Roden, D. M., & Crawford, D. C. (2010) · Bioinformatics

Genetic Associations and EpidemiologyHealth, Environment, Cognitive Aging

Cited by 1,219

Artificial intelligence, bias and clinical safety

Challen, R., Denny, J., Pitt, M., Gompels, L., Edwards, T., & Tsaneva-Atanasova, K. (2019) · BMJ Quality & Safety

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 956

Genomic data in the all of us research program

The All of Us Research Program Genomics Investigators, Manuscript Writing Group, Bick, A. G., Metcalf, G. A., Mayo, K. R., Lichtenstein, L., Rura, S., Carroll, R. J., Musick, A., Linder, J. E., et al. (2024) · Nature

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 829

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Suzuki, K., Hatzikotoulas, K., Southam, L., Taylor, H. J., Yin, X., Lorenz, K. M., Mandla, R., Huerta-Chagoya, A., Melloni, G. E. M., Kanoni, S., et al. (2024) · Nature

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 606

Data from clinical notes: a perspective on the tension between structure and flexible documentation

Rosenbloom, S. T., Denny, J. C., Xu, H., Lorenzi, N., Stead, W. W., & Johnson, K. B. (2011) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsNursing Diagnosis and Documentation

Cited by 404

PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study

Schmidt, A. F., Swerdlow, D. I., Holmes, M. V., Patel, R. S., Fairhurst-Hunter, Z., Lyall, D. M., Hartwig, F. P., Horta, B. L., Hyppönen, E., Power, C., et al. (2017) · The Lancet Diabetes & Endocrinology

Lipoproteins and Cardiovascular HealthGenetic Associations and Epidemiology

Cited by 380

Electronic Medical Records for Genetic Research: Results of the eMERGE Consortium

Kho, A. N., Pacheco, J. A., Peissig, P. L., Rasmussen, L., Newton, K. M., Weston, N., Crane, P. K., Pathak, J., Chute, C. G., Bielinski, S. J., et al. (2011) · Science Translational Medicine

Electronic Health Records SystemsGenetic Associations and Epidemiology

Cited by 336

The phenotypic legacy of admixture between modern humans and Neandertals

Simonti, C. N., Vernot, B., Bastarache, L., Bottinger, E., Carrell, D. S., Chisholm, R. L., Crosslin, D. R., Hebbring, S. J., Jarvik, G. P., Kullo, I. J., et al. (2016) · Science

Pleistocene-Era Hominins and ArchaeologyGenetic Associations and Epidemiology

Cited by 330

Electronic health records-driven phenotyping: challenges, recent advances, and perspectives

Pathak, J., Kho, A. N., & Denny, J. C. (2013) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsMachine Learning in Healthcare

Cited by 274

Diversity and inclusion for the All of Us research program: A scoping review

Mapes, B. M., Foster, C. S., Kusnoor, S. V., Epelbaum, M. I., AuYoung, M., Jenkins, G., Lopez-Class, M., Richardson-Heron, D., Elmi, A., Surkan, K., et al. (2020) · PLOS ONE

Ethics in Clinical ResearchRace, Genetics, and Society

Cited by 273

Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance

Wei, W.-Q., Teixeira, P. L., Mo, H., Cronin, R. M., Warner, J. L., & Denny, J. C. (2016) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 230

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records

Van Driest, S. L., Wells, Q. S., Stallings, S., Bush, W. S., Gordon, A., Nickerson, D. A., Kim, J. H., Crosslin, D. R., Jarvik, G. P., Carrell, D. S., et al. (2016) · JAMA

Cardiac electrophysiology and arrhythmiasGenomics and Rare Diseases

Cited by 170

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Volpi, S., Bult, C. J., Chisholm, R. L., Deverka, P. A., Ginsburg, G. S., Jacob, H. J., Kasapi, M., McLeod, H. L., Roden, D. M., Williams, M. S., et al. (2018) · Clinical Pharmacology & Therapeutics

Pharmacogenetics and Drug MetabolismGenetic Associations and Epidemiology

Cited by 135

Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants

Karnes, J. H., Bastarache, L., Shaffer, C. M., Gaudieri, S., Xu, Y., Glazer, A. M., Mosley, J. D., Zhao, S., Raychaudhuri, S., Mallal, S., et al. (2017) · Science Translational Medicine

Genetic Associations and EpidemiologyDiabetes and associated disorders

Cited by 126

A hybrid system for temporal information extraction from clinical text

Tang, B., Wu, Y., Jiang, M., Chen, Y., Denny, J. C., & Xu, H. (2013) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 117

Development and evaluation of an ensemble resource linking medications to their indications

Wei, W.-Q., Cronin, R. M., Xu, H., Lasko, T. A., Bastarache, L., & Denny, J. C. (2013) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesElectronic Health Records Systems

Cited by 106

Mining 100 million notes to find homelessness and adverse childhood experiences: 2 case studies of rare and severe social determinants of health in electronic health records

Bejan, C. A., Angiolillo, J., Conway, D., Nash, R., Shirey-Rice, J. K., Lipworth, L., Cronin, R. M., Pulley, J., Kripalani, S., Barkin, S., et al. (2018) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 106