Wei, Wei-Qi

Precision medicine, AI, and the future of personalized health care

Johnson, K. B., Wei, W., Weeraratne, D., Frisse, M. E., Misulis, K., Rhee, K., Zhao, J., & Snowdon, J. L. (2021) · Clinical and Translational Science

Artificial Intelligence in Healthcare and EducationTechnology and Human Factors in Education and Health

Cited by 1,854

The power of genetic diversity in genome-wide association studies of lipids

Graham, S. E., Clarke, S. L., Wu, K.-H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., et al. (2021) · Nature

Genetic Associations and EpidemiologyLipoproteins and Cardiovascular Health

Cited by 972

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

Clinical and pharmacogenetic predictors of circulating atorvastatin and rosuvastatin concentrations in routine clinical care

DeGorter, M. K., Tirona, R. G., Schwarz, U. I., Choi, Y.-H., Dresser, G. K., Suskin, N., Myers, K., Zou, G., Iwuchukwu, O., Wei, W.-Q., et al. (2013) · Circulation: Cardiovascular Genetics

Pharmacogenetics and Drug MetabolismLipoproteins and Cardiovascular Health

Cited by 195

Impact of data fragmentation across healthcare centers on the accuracy of a high-throughput clinical phenotyping algorithm for specifying subjects with type 2 diabetes mellitus

Wei, W.-Q., Leibson, C. L., Ransom, J. E., Kho, A. N., Caraballo, P. J., Chai, H. S., Yawn, B. P., Pacheco, J. A., & Chute, C. G. (2012) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 112

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

Leveraging generative AI to prioritize drug repurposing candidates for Alzheimer's disease with real-world clinical validation

Yan, C., Grabowska, M. E., Dickson, A. L., Li, B., Wen, Z., Roden, D. M., Michael Stein, C., Embí, P. J., Peterson, J. F., Feng, Q., et al. (2024) · npj Digital Medicine

Alzheimer's disease research and treatmentsComputational Drug Discovery Methods

Cited by 73

Drug repurposing for Alzheimer’s disease from 2012–2022—a 10-year literature review

Grabowska, M. E., Huang, A., Wen, Z., Li, B., & Wei, W.-Q. (2023) · Frontiers in Pharmacology

Alzheimer's disease research and treatmentsCholinesterase and Neurodegenerative Diseases

Cited by 55

Associations of Genetically Predicted Lp(a) (Lipoprotein [a]) Levels With Cardiovascular Traits in Individuals of European and African Ancestry

Satterfield, B. A., Dikilitas, O., Safarova, M. S., Clarke, S. L., Tcheandjieu, C., Zhu, X., Bastarache, L., Larson, E. B., Justice, A. E., Shang, N., et al. (2021) · Circulation: Genomic and Precision Medicine

Lipoproteins and Cardiovascular HealthGenetic Associations and Epidemiology

Cited by 40

Representing and utilizing clinical textual data for real world studies: An OHDSI approach

Keloth, V. K., Banda, J. M., Gurley, M., Heider, P. M., Kennedy, G., Liu, H., Liu, F., Miller, T., Natarajan, K., V Patterson, O., et al. (2023) · Journal of Biomedical Informatics

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 16