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Contributed Papers

Advances in Statistical Machine Learning Methods for Complex Data Scenarios

Mon, Aug 5, 2:00 PM - 3:50 PM

Pedro OrozcoDelPinoChair

Biometrics Section

7 Presentations

Fair Risk Predictions for Underrepresented Asian American Populations using Electronic Health Record

2:05 PM - 2:20 PM

Flexible Kernel-Based Expectile Regression with Inference for Dependent Data

2:20 PM - 2:35 PM

Benjamin Osafo Agyare

Co-authors: Kerby Shedden (University of Michigan)

Gradient boosting for group testing data

2:35 PM - 2:50 PM

Erica Porter (Clemson University)

Co-authors: Christopher McMahan, Joshua Tebbs (University of South Carolina), Christopher Bilder

Identifying when prediction models extrapolate

2:50 PM - 3:05 PM

Grace Lyden (Hennepin Healthcare Research Institute)

Co-authors: Nicholas Wood (Hennepin Healthcare Research Institute)

Potential of random survival forest in providing reliable predictors in a very small dataset

3:05 PM - 3:20 PM

Cinzia Anna Maria Papappicco

Co-authors: Giulia Lorenzoni (Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic and Vascular), MariaVittoria Chiaruttini (University of Padua), Dario Gregori (University of Padova)

Rank-based methods for comparing within-source distributions for few-shot learning algorithms

3:20 PM - 3:35 PM

Co-authors: Christopher Saunders (South Dakota State University), JoAnn Buscaglia (FBI Laboratory Division)

Rashomon sets for decision trees with counterfactual explanations for examining HIV-related stigma

3:35 PM - 3:50 PM

Co-authors: Ash Abebe (Auburn University), Jessica Busler (Brigham and Women's Hospital), F. Stephen Dobson (Auburn University)

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