Kho, Abel N.

Defining the role of common variation in the genomic and biological architecture of adult human height

The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 1,853

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Mahajan, A., Spracklen, C. N., Zhang, W., Ng, M. C. Y., Petty, L. E., Kitajima, H., Yu, G. Z., Rüeger, S., Speidel, L., Kim, Y. J., et al. (2022) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 704

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

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

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

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

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

An exploratory survey about using ChatGPT in education, healthcare, and research

Hosseini, M., Gao, C. A., Liebovitz, D. M., Carvalho, A. M., Ahmad, F. S., Luo, Y., MacDonald, N., Holmes, K. L., & Kho, A. (2023) · PLOS ONE

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Education

Cited by 238

An exploratory survey about using ChatGPT in education, healthcare, and research

Hosseini, M., Gao, C. A., Liebovitz, D. M., Carvalho, A. M., Ahmad, F. S., Luo, Y., MacDonald, N., Holmes, K. L., & Kho, A. (2023) · PLoS ONE

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Education

Cited by 238

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

Practical challenges in integrating genomic data into the electronic health record

Kho, A. N., Rasmussen, L. V., Connolly, J. J., Peissig, P. L., Starren, J., Hakonarson, H., & Hayes, M. G. (2013) · Genetics in Medicine

Electronic Health Records SystemsGenomics and Rare Diseases

Cited by 108

Early prediction of acute kidney injury following ICU admission using a multivariate panel of physiological measurements

Zimmerman, L. P., Reyfman, P. A., Smith, A. D. R., Zeng, Z., Kho, A., Sanchez-Pinto, L. N., & Luo, Y. (2019) · BMC Medical Informatics and Decision Making

Acute Kidney Injury ResearchMachine Learning in Healthcare

Cited by 100

An evaluation of recurrent diabetic ketoacidosis, fragmentation of care, and mortality across Chicago, Illinois

Mays, J. A., Jackson, K. L., Derby, T. A., Behrens, J. J., Goel, S., Molitch, M. E., Kho, A. N., & Wallia, A. (2016) · Diabetes Care

Diabetes Management and ResearchDiabetes Management and Education

Cited by 95

A Regional Informatics Platform for Coordinated Antibiotic-Resistant Infection Tracking, Alerting, and Prevention

Kho, A. N., Doebbeling, B. N., Cashy, J. P., Rosenman, M. B., Dexter, P. R., Shepherd, D. C., Lemmon, L., Teal, E., Khokar, S., & Overhage, J. M. (2013) · Clinical Infectious Diseases

Infection Control in HealthcareAntibiotic Use and Resistance

Cited by 23

A Taxonomy for External Support for Practice Transformation

Solberg, L. I., Kuzel, A., Parchman, M. L., Shelley, D. R., Dickinson, W. P., Walunas, T. L., Nguyen, A. M., Fagnan, L. J., Cykert, S., Cohen, D. J., et al. (2021) · The Journal of the American Board of Family Medicine

Health Policy Implementation ScienceClinical practice guidelines implementation

Cited by 18

Cohort study examining social determinants of health and their association with mortality among hospitalised adults in New York and California

Wang, A., French, D., Black, B., & Kho, A. N. (2025) · BMJ Public Health

Health disparities and outcomesPublic Health and Social Inequalities

Cited by 1