Evaluation of using a collective approach when selecting biomarker features from machine learning models. - Carly A. Bobak; Jane E. Hill (BIBM, 2018)

Investigating Random Forest Classification on Publicly Available Tuberculosis Data to Uncover Robust Transcriptional Biomarkers. - Carly A. Bobak; Alexander J. Titus; Jane E. Hill (HEALTHINF, 2018)

A New Dimension of Breast Cancer Epigenetics - Applications of Variational Autoencoders with DNA Methylation. - Alexander J. Titus; Carly A. Bobak; Brock C. Christensen (BIOINFORMATICS, 2018)

Comparison of common machine learning models for classification of tuberculosis using transcriptional biomarkers from integrated datasets. - Carly A. Bobak; Alexander J. Titus; Jane E. Hill (Appl. Soft Comput., 2019)

Assessment of Imputation Methods for Missing Gene Expression Data in Meta-Analysis of DistinctCohorts of Tuberculosis Patients. - Carly A. Bobak; Lauren McDonnell; Matthew D. Nemesure; Justin Lin; Jane E. Hill (PSB, 2020)

Raising the stakeholders: Improving patient outcomes through interprofessional collaborations in AI for healthcare. - Carly A. Bobak; Marek Svoboda; Kristine A. Giffin; Dennis P. Wall; Jason H. Moore (PSB, 2021)

Replicability of Differentially Expressed Genes Versus Biological Pathways Biomarkers in Diagnosing Sepsis. - Kelsey Winkeler; Carly A. Bobak (BIOINFORMATICS, 2022)

GRANDPA: GeneRAtive network sampling using degree and property augmentation applied to the analysis of partially confidential healthcare networks. - Carly A. Bobak; Yifan Zhao; Joshua J. Levy; A. James O'Malley (Appl. Netw. Sci., 2023)