Emmanuel N. Nartey, Ph.D. is a Research Scientist for the Center for Biostatistics and Health Data Science. He began his career at CBHDS in May 2024, after graduating with his Ph.D. in Statistics and Analytics from the Department of Statistics, Actuarial, and Data Sciences at Central Michigan University. His research interests include supervised and unsupervised machine learning, statistical computing, complex survey data analysis, generalized linear models, and pharmacoepidemiology. His dissertation studied internal indices for validating clustering solutions and using those indices to guide feature selection for classification. Emmanuel has experience working with national health surveys and electronic health records and has contributed to research studies in different health areas including chronic disease management, nutritional psychology, pharmacoepidemiology, eating disorders, HPV vaccination, and Medicare payments.
Vaughn-Cooke, M., & Nartey, E. Beyond Diagnoses: Identifying Functional Subgroups Among Adults with Chronic Conditions Using NHANES Data. (manuscript in preparation)
Nartey, E. N., Lee, C., & Famoye, F. A comparative review of some internal validation techniques for determining the number of clusters in numeric data. (manuscript in preparation)
Nartey, E. N., Lee, C., & Famoye, F. Numeric feature selection via the Average Silhouette Score towards optimal classification in machine learning. (manuscript in preparation)
Dell, G., Landgraf, K., Ngounly, C., Choi, H., Waymack, S., Nartey, E., Hanlon, A., Patterson, A., & Faltin, F. An Evaluation of FDA’s FAERS Database’s Ability to Identify Safety Signals Over Time Using Montelukast’s Neurotoxicity Issues. (manuscript in preparation)
Kolb, R., Nartey, E., Lozano, A., Hanlon, A., Ramirez, V., & Parma, V. Chemosensation with glucagon-like-peptide-1 receptor agonists: A pharmacovigilance assessment. Laryngoscope. (submitted)
Hutelin, Z., Ahrens, M., Baugh M. E., Nartey, E., Heald, D. L., Hanlon, A., DiFeliceantonio, A. G. Ultraprocessed foods elicit distinct metabolic and neural responses when compared to non-ultraprocessed foods. Nature Metabolism. (manuscript under review)
Gearhardt, A. N., Hutelin, Z., Nartey, E., Ahrens, M., Baugh, M., Fazzino, T., LaFata, E., Sonneville, K., & DiFeliceantonio, A. (2026). Nutritional Characteristics of Foods with Addictive Potential: A Machine Learning Approach. American Journal of Public Health, 116(7), 950. DOI: 10.2105/AJPH.2026.308500
Gainey, M., Stettinius, A., Holmes, H., Nartey, E., Stayrook, S., Maxwell, A., Vlaisavljevich, E. & Rao, J. (2026). Evaluation and Characterization of a Novel DNA Lysis Technique for Extraction of Nontuberculous Mycobacteria DNA. Open Forum Infectious Diseases 2026 Jan 11; 13 (Suppl 1) :ofaf695.1861. DOI: 10.1093/ofid/ofaf695.1861
Palit, S., Sufyani, T., Inungu, J. N., Cheng, C. I., & Nartey, E. (2024). Behavioral Determinants of Childhood Obesity in the United States: An Exploratory Study. Journal of Obesity, 2024(1), 9224425. DOI: 10.1155/2024/9224425
Ameh, G., Nartey, E., Inungu, J., Shayestah, J. & Uchechukwu, O. (2023). Racial Disparities in Oral Health; Analysis of 2020 Behavioral Risk Factor Surveillance System. Acta Scientific Dental Sciences, Vol. 7, pp. 29-39. DOI: 10.31080/ASDS.2023.07.1551