118 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of ChicagoUS8 papers
- The University of Texas at AustinUS4 papers
- Cytel (United States)US3 papers
- University of Illinois ChicagoUS3 papers
- Colorado State UniversityUS2 papers
- Fudan UniversityCN2 papers
- Harvard UniversityUS2 papers
- Cancer Research And BiostatisticsUS1 paper
- East China Normal UniversityCN1 paper
- Florida International UniversityUS1 paper
- Galena Biopharma (United States)US1 paper
- Georgia Institute of TechnologyUS1 paper
14 papers
Monitoring Adverse Events Through Bayesian Nonparametric Clustering Across Studies
Shijie Yuan, Kevin Roberts, Noirrit Kiran Chandra +2
We introduce a Bayesian nonparametric inference approach for aggregate adverse event (AE) monitoring across studies. The proposed model seamlessly integrates external data from his…
SIMBA -- A Bayesian Decision Framework for the Identification of Optimal Biomarker Subgroups for Cancer Basket Clinical Trials
Shijie Yuan, Jiaxin Liu, Zhihua Gong +4
We consider basket trials in which a biomarker-targeting drug may be efficacious for patients across different disease indications. Patients are enrolled if their cells exhibit som…
VIGMA: An Open-Access Framework for Visual Gait and Motion Analytics
Kazi Shahrukh Omar, Shuaijie Wang, Ridhuparan Kungumaraju +2
Gait disorders are commonly observed in older adults, who frequently experience various issues related to walking. Additionally, researchers and clinicians extensively investigate…
Pharmacometrics-Enabled DOse OPtimization (PEDOOP) for Seamless Phase I-II Trials in Oncology
Shijie Yuan, Zhanbo Huang, Jiaxin Liu +1
We consider a dose-optimization design for first-in-human oncology trial that aims to identify a suitable dose for late-phase drug development. The proposed approach, called the Ph…
On adjustment for temperature in heatwave epidemiology: a new method and toward clarification of methods to estimate health effects of heatwaves
Honghyok Kim, Michelle Bell
Defining the effect of exposure of interest and selecting an appropriate estimation method are prerequisite for causal inference. Understanding the ways in which association betwee…
The Backfill i3+3 Design for Dose-Finding Trials in Oncology
Jiaxin Liu, Shijie Yuan, B. Nebiyou Bekele +1
We consider a formal statistical design that allows simultaneous enrollment of a main cohort and a backfill cohort of patients in a dose-finding trial. The goal is to accumulate mo…
On Bayesian Sequential Clinical Trial Designs
Tianjian Zhou, Yuan Ji
Clinical trials usually involve sequential patient entry. When designing a clinical trial, it is often desirable to include a provision for interim analyses of accumulating data wi…
Network Interventions: Applying Network Science for Pragmatic Action in Public Administration and Policy
Michael D. Siciliano, Travis A. Whetsell
Public management and policy scholars have engaged in extensive development of theory and empirical study of networks and collaborative systems of governance. This scholarship has…
BaySize: Bayesian Sample Size Planning for Phase I Dose-Finding Trials
Xiaolei Lin, Jiaying Lyu, Shijie Yuan +2
We propose BaySize, a sample size calculator for phase I clinical trials using Bayesian models. BaySize applies the concept of effect size in dose finding, assuming the MTD is defi…
The Ci3+3 Design for Dual-Agent Combination Dose-Finding Clinical Trials
Shijie Yuan, Tianjian Zhou, Yawen Lin +1
We propose a rule-based statistical design for combination dose-finding trials with two agents. The Ci3+3 design is an extension of the i3+3 design with simple decision rules compa…
Lessons Learned from the Bayesian Design and Analysis for the BNT162b2 COVID-19 Vaccine Phase 3 Trial
Yuan Ji, Shijie Yuan
The phase III BNT162b2 mRNA COVID-19 vaccine trial is based on a Bayesian design and analysis, and the main evidence of vaccine efficacy is presented in Bayesian statistics. Confus…
Machine-learned epidemiology: real-time detection of foodborne illness at scale
Adam Sadilek, Stephanie Caty, Lauren DiPrete +6
Machine learning has become an increasingly powerful tool for solving complex problems, and its application in public health has been underutilized. The objective of this study is…
Aequitas: A Bias and Fairness Audit Toolkit
Pedro Saleiro, Benedict Kuester, Loren Hinkson +5
Recent work has raised concerns on the risk of unintended bias in AI systems being used nowadays that can affect individuals unfairly based on race, gender or religion, among other…
Minimal sufficient causation and directed acyclic graphs
Tyler J. VanderWeele, James M. Robins
Notions of minimal sufficient causation are incorporated within the directed acyclic graph causal framework. Doing so allows for the graphical representation of sufficient causes a…