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Contributed Papers

Risk Analysis in Health, Environment and Financial Research

Tue, Aug 5, 2:00 PM - 3:50 PM Room CC-201A Music City Center

Thomas FisherChair

Section on Risk Analysis

7 Presentations

Combining safety signals in drug clinical trials and postmarket surveillance using Bayesian modeling

2:05 PM - 2:20 PM

Co-authors: Dong Wang (FDA National Center for Toxicological Research (NCTR)), Dong Wang (FDA National Center for Toxicological Research (NCTR))

adverse event postmarket surveillance Bayesian model clinical trial

Estimating the Risk of Cancer With and Without a Screening History

2:20 PM - 2:35 PM

Co-authors: Dongfeng Wu (University of Louisville), Dongfeng Wu (University of Louisville)

incidence risk sensitivity sojourn time transition probability density

Pointwise Predictive Density Calibrated-Power Prior for Dynamic Borrowing of Historical Data

2:35 PM - 2:50 PM

Co-authors: Shixuan Wang, Shixuan Wang, Jing Zhang (Miami University), Bin Zhang (Cincinnati Children’s Hospital Medical Center), Emily Kang (University of Cincinnati)

Bayesian p-value Calibrated power prior Congruence measure Dynamic historical borrowing

Weighted quantile regression to evaluate responsiveness of health effects due to chemical exposure

2:50 PM - 3:05 PM

Co-authors: Geoffrey Peterson, Geoffrey Peterson, Chelsea Weitekamp (U.S. Environmental Protection Agency), Krista Christensen (US EPA), Catheryne Chiang (US EPA), Laura Carlson (US EPA), Geniece Lehmann (US EPA)

Systematic review Quantile regression Toxicology PCB

Modeling Directional Dependence of Extreme Events

3:05 PM - 3:20 PM

Co-authors: Maxime Nicolas, Maxime Nicolas

Directional Dependence Tail Dependence Copula Tail Expectation

Evaluation of the effectiveness of AI methods in detecting and forecasting anomalies in the stock ma

3:20 PM - 3:35 PM

Co-authors: Malgorzata Tarczynska-Luniewska (University of Szczecin), Malgorzata Tarczynska-Luniewska (University of Szczecin)

AI econometric models stock market anomalies stock market indices

Optimizing Credit Risk Classification Using Machine Learning Techniques

3:35 PM - 3:50 PM

Co-authors: Nzubechukwu Ohalete, Nzubechukwu Ohalete, Nzubechukwu Ohalete, Faruk Muritala (Kennesaw State University), Herman Ray

Machine Learning (ML)Creditworthy Classification Credit Risk Financial Institutions Financial Risk Management

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