Shenkman, Elizabeth A.

A large language model for electronic health records

Yang, X., Chen, A., PourNejatian, N., Shin, H. C., Smith, K. E., Parisien, C., Compas, C., Martin, C., Costa, A. B., Flores, M. G., et al. (2022) · npj Digital Medicine

Machine Learning in HealthcareTopic Modeling

Cited by 847

A study of generative large language model for medical research and healthcare

Peng, C., Yang, X., Chen, A., Smith, K. E., PourNejatian, N., Costa, A. B., Martin, C., Flores, M. G., Zhang, Y., Magoc, T., et al. (2023) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 408

The All of Us Research Program: Data quality, utility, and diversity

Ramirez, A. H., Sulieman, L., Schlueter, D. J., Halvorson, A., Qian, J., Ratsimbazafy, F., Loperena, R., Mayo, K., Basford, M., Deflaux, N., et al. (2022) · Patterns

Electronic Health Records SystemsEthics in Clinical Research

Cited by 352

Comparative Effectiveness of Aspirin Dosing in Cardiovascular Disease

Jones, W. S., Mulder, H., Wruck, L. M., Pencina, M. J., Kripalani, S., Muñoz, D., Crenshaw, D. L., Effron, M. B., Re, R. N., Gupta, K., et al. (2021) · New England Journal of Medicine

Antiplatelet Therapy and Cardiovascular DiseasesAcute Myocardial Infarction Research

Cited by 307

Algorithmic fairness in computational medicine

Xu, J., Xiao, Y., Wang, W. H., Ning, Y., Shenkman, E. A., Bian, J., & Wang, F. (2022) · eBioMedicine

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 170

Early prediction of Alzheimer's disease and related dementias using real-world electronic health records

Li, Q., Yang, X., Xu, J., Guo, Y., He, X., Hu, H., Lyu, T., Marra, D., Miller, A., Smith, G., et al. (2023) · Alzheimer's & Dementia

Machine Learning in HealthcareDementia and Cognitive Impairment Research

Cited by 113

OneFlorida Clinical Research Consortium: linking a clinical and translational science institute with a community-based distributive medical education model

Shenkman, E., Hurt, M., Hogan, W., Carrasquillo, O., Smith, S., Brickman, A., & Nelson, D. (2018) · Academic Medicine

Health and Medical Research ImpactsHealth Policy Implementation Science

Cited by 97

International Classification of Diseases, Tenth Revision, Clinical Modification social determinants of health codes are poorly used in electronic health records

Guo, Y., Chen, Z., Xu, K., George, T. J., Wu, Y., Hogan, W., Shenkman, E. A., & Bian, J. (2020) · Medicine

Medical Coding and Health InformationElectronic Health Records Systems

Cited by 95

Assessing the practice of data quality evaluation in a national clinical data research network through a systematic scoping review in the era of real-world data

Bian, J., Lyu, T., Loiacono, A., Viramontes, T. M., Lipori, G., Guo, Y., Wu, Y., Prosperi, M., George, T. J., Harle, C. A., et al. (2020) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsData Quality and Management

Cited by 92

Effect of Higher-Dose Ivermectin for 6 Days vs Placebo on Time to Sustained Recovery in Outpatients With COVID-19: A Randomized Clinical Trial

Naggie, S., Boulware, D. R., Lindsell, C. J., Stewart, T. G., Slandzicki, A. J., Lim, S. C., Cohen, J., Kavtaradze, D., Amon, A. P., Gabriel, A., et al. (2023) · JAMA

COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 Research

Cited by 79

GatorTron: A Large Language Model for Clinical Natural Language Processing

Yang, X., PourNejatian, N., Shin, H. C., Smith, K. E., Parisien, C., Compas, C., Martin, C., Flores, M. G., Zhang, Y., Magoc, T., et al. (2022) · medRxiv

Machine Learning in HealthcareTopic Modeling

Cited by 33

Geographic variation and racial disparities in adoption of newer glucose-lowering drugs with cardiovascular benefits among US Medicare beneficiaries with type 2 diabetes

Chen, W.-H., Li, Y., Yang, L., Allen, J. M., Shao, H., Donahoo, W. T., Billelo, L., Hu, X., Shenkman, E. A., Bian, J., et al. (2024) · PLOS ONE

Diabetes Treatment and ManagementDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 17

A Fair Individualized Polysocial Risk Score for Identifying Increased Social Risk in Type 2 Diabetes

Huang, Y., Guo, J., Donahoo, W. T., Lee, Y. A., Fan, Z., Lu, Y., Chen, W.-H., Tang, H., Bilello, L., Saguil, A. A., et al. (2024) · Nature Communications

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 14

Developing a computable phenotype for identifying children, adolescents, and young adults with diabetes using electronic health records in the DiCAYA Network.

Shao, H., Thorpe, L. E., Islam, S., Bian, J., Guo, Y., Li, P., Bost, S., Dabelea, D., Conway, R., Crume, T., et al. (2025) · Diabetes Care

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 8