Ryu, Euijung

Genome-wide association study identifies 30 loci associated with bipolar disorder

eQTLGen Consortium, Stahl, E. A., BIOS Consortium, the Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Breen, G., Forstner, A. J., McQuillin, A., Ripke, S., Trubetskoy, V., Mattheisen, M., et al. (2019) · Nature Genetics

Bipolar Disorder and TreatmentGenetic Associations and Epidemiology

Cited by 1,519

Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

23andMe Research Team, Walters, R. K., Polimanti, R., Johnson, E. C., McClintick, J. N., Adams, M. J., Adkins, A. E., Aliev, F., Bacanu, S.-A., Batzler, A., et al. (2018) · Nature Neuroscience

Genetic Associations and EpidemiologySubstance Abuse Treatment and Outcomes

Cited by 632

Extracting social determinants of health from electronic health records using natural language processing: a systematic review

Patra, B. G., Sharma, M. M., Vekaria, V., Adekkanattu, P., Patterson, O. V., Glicksberg, B., Lepow, L. A., Ryu, E., Biernacka, J. M., Furmanchuk, A., et al. (2021) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 248

Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders

Hatoum, A. S., Colbert, S. M. C., Johnson, E. C., Huggett, S. B., Deak, J. D., Pathak, G. A., Jennings, M. V., Paul, S. E., Karcher, N. R., Hansen, I., et al. (2023) · Nature Mental Health

Genetic Associations and EpidemiologySubstance Abuse Treatment and Outcomes

Cited by 241

Application of a Natural Language Processing Algorithm to Asthma Ascertainment. An Automated Chart Review

Wi, C.-I., Sohn, S., Rolfes, M. C., Seabright, A., Ryu, E., Voge, G., Bachman, K. A., Park, M. A., Kita, H., Croghan, I. T., et al. (2017) · American Journal of Respiratory and Critical Care Medicine

Asthma and respiratory diseasesMedical Coding and Health Information

Cited by 88

Assessing Socioeconomic Bias in Machine Learning Algorithms in Health Care: A Case Study of the HOUSES Index

Juhn, Y. J., Ryu, E., Wi, C.-I., King, K. S., Malik, M., Romero-Brufau, S., Weng, C., Sohn, S., Sharp, R. R., & Halamka, J. D. (2022) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareEthics and Social Impacts of AI

Cited by 83

Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial

Seol, H. Y., Shrestha, P., Muth, J. F., Wi, C.-I., Sohn, S., Ryu, E., Park, M., Ihrke, K., Moon, S., King, K., et al. (2021) · PLOS ONE

Asthma and respiratory diseasesElectronic Health Records Systems

Cited by 82

Natural language processing for asthma ascertainment in different practice settings

Wi, C.-I., Sohn, S., Ali, M., Krusemark, E., Ryu, E., Liu, H., & Juhn, Y. J. (2018) · The Journal of Allergy and Clinical Immunology In Practice

Asthma and respiratory diseasesMedical Coding and Health Information

Cited by 62

Extracting social support and social isolation information from clinical psychiatry notes: comparing a rule-based natural language processing system and a large language model

Patra, B. G., Lepow, L. A., Kasi Reddy Jagadeesh Kumar, P., Vekaria, V., Sharma, M. M., Adekkanattu, P., Fennessy, B., Hynes, G., Landi, I., Sanchez-Ruiz, J. A., et al. (2025) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 32