PERSONNEL

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Seo Baik, PhD

Computational Health Research Branch
Biostatistician

Contact InformationNihbc 38A - Lister Hill 10s1010 301.827.4999
seo.baik@nih.gov


Expertise and Research Interests:

In June 2015 Seo Baik, Ph.D., joined the Lister Hill National Center for Biomedical Communications at the National Library of Medicine. Dr. Baik received his doctorate degree in Statistics from University of Pittsburgh. He is a lead investigator in the project characterizing the effects of biologics and drugs in the Medicare population. He has rich experience with the survival data analysis and the evaluation of large databases – especially Medicare’s huge trove of clinical and administrative data. His research interests include applications of deep learning and/or extended Cox regression analysis in the area of comparative efficacy and safety of prescription drugs and cost-effectiveness of healthcare. He works in the Computational Health Research Branch with Dr. Clem McDonald and others.

Honors and Awards:

Received an individual NLM Special Act or Service Award in 2017 for completing the analysis and interpretation of several biomedical statistical projects.


Publications:

Fung KW, Baye F, Baik SH, McDonald CJ . Nirmatrelvir and Molnupiravir and Post–COVID-19 Condition in Older Patients. JAMA Internal Medicine. https://doi.org/10.1001/JAMAINTERNMED.2023.5099.

Fung KW, Baye F, Baik SH, Zheng Z, McDonald CJ . Prevalence and characteristics of long COVID in elderly patients: An observational cohort study of over 2 million adults in the US. PLoS Medicine, 20(4). https://doi.org/10.1371/JOURNAL.PMED.1004194.

McDonald CJ, Baik SH, Zheng Z, Amos L, Luan X, Marsolo K, Qualls L. Mis-mappings between a producer’s quantitative test codes and LOINC codes and an algorithm for correcting them. Journal of the American Medical Informatics Association, 2022;, ocac215, https://doi.org/10.1093/jamia/ocac215.

Fung KW, Baik SH, Baye F, Zheng Z, Huser V, McDonald CJ. Effect of common maintenance drugs on the risk and severity of COVID-19 in elderly patients. PLoS ONE 17(4): e0266922. https://doi.org/10.1371/journal.pone.0266922.

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