A call for biological data mining approaches in epidemiology. - Shannon M. Lynch; Jason H. Moore (BioData Min., 2016)

A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments. - Ryan J. Urbanowicz; Pranshu Suri; Yuhan Cui; Jason H. Moore; Karen Ruth; Rachael Stolzenberg-Solomon; Shannon M. Lynch (CoRR, 2020)

LCS-DIVE: An Automated Rule-based Machine Learning Visualization Pipeline for Characterizing Complex Associations in Classification. - Robert Zhang 004; Rachael Stolzenberg-Solomon; Shannon M. Lynch; Ryan J. Urbanowicz (CoRR, 2021)

STREAMLINE: An Automated Machine Learning Pipeline for Biomedicine Applied to Examine the Utility of Photography-Based Phenotypes for OSA Prediction Across International Sleep Centers. - Ryan J. Urbanowicz; Harsh Bandhey; Brendan T. Keenan; Greg Maislin; Sy Hwang; Danielle L. Mowery; Shannon M. Lynch; Diego R. Mazzotti; Fang Han; Qing Yun Li; Thomas Penzel; Sergio Tufik; et al. (CoRR, 2023)