My main research interest is developing machine-learning methodology for prediction modeling. Specifically, my recent work focuses on extending decision tree and random forest algorithms for clustered and longitudinal data. I enjoy collaborations with clinical researchers and basic scientists.
Jaime Lynn Speiser, MSc, PhD
- Assistant Professor, Biostatistics and Data Science

Jaime Lynn Speiser, MSc, PhD
Research Interests
- Liver Failure, Acute
- Models, Theoretical
- Models, Statistical
- Aging
- Predictive Analytics
- Positions
- Assistant Professor, Biostatistics and Data Science
- Departments and Affiliations
- Biostatistics and Data Science
- Sticht Center for Healthy Aging and Alzheimer's Prevention
- Center for Biomedical Informatics
Research
- Food Insecurity Is Associated with an Increased Prevalence of Comorbid Medical Conditions in Obese Adults: NHANES 2007-2014. Palakshappa D, Speiser JL, Rosenthal GE, Vitolins MZ. J Gen Intern Med. 2019 08; 34(8):1486-1493.
- Predicting daily outcomes in acetaminophen-induced acute liver failure patients with machine learning techniques. Speiser JL, Karvellas CJ, Wolf BJ, Chung D, Koch DG, Durkalski VL. Comput Methods Programs Biomed. 2019 Jul; 175:111-120.
- J Gen Intern Med. Palakshappa, D; Speiser, J; Rosenthal, G; Vitolins, M. Food insecurity is associated with an increased risk of comorbid medical conditions in obese individuals. 2019 Jan; 1; :1-8.
- Comput Methods Programs Biomed. Speiser, J; Karvellas, C; Wolf, B; Chung, D; Koch, D; Durkalski, V. Predicting daily outcomes in acetaminophen-induced acute liver failure patients with machine learning techniques. 2019 Jan; 1; 1(175):111-120.
- Expert Syst Appl. Speiser, J; Miller, M; Tooze, J; Ip, E. A comparison of random forest variable selection methods for classification modeling. 2019 Jan; 1; 134:93-101.