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Picture for Rachael Stolzenberg-Solomon

Rachael Stolzenberg-Solomon

LCS-DIVE: An Automated Rule-based Machine Learning Visualization Pipeline for Characterizing Complex Associations in Classification

Apr 26, 2021
Robert Zhang, Rachael Stolzenberg-Solomon, Shannon M. Lynch, Ryan J. Urbanowicz

* 21 pages, 11 figures, submitted for review on 4/26/21 

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A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments

Sep 08, 2020
Ryan J. Urbanowicz, Pranshu Suri, Yuhan Cui, Jason H. Moore, Karen Ruth, Rachael Stolzenberg-Solomon, Shannon M. Lynch

* 22 pages, 12 figures 

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