17th Annual Innovations in Design, Analysis, and Dissemination: Frontiers in Biostatistics & Data Science Meeting

Sponsors:The University of Kansas Medical Center Department of Biostatistics & Data Science, Kansas Western-Missouri Chapter of the American Statistical Association, University of Kansas Cancer Center, Quantitative Omics Core that supports the Kansas Institute for Precision Medicine, K-INBRE, and EMB Statistical Solutions, LLC.

Program at a glance:

Day 1 Program
Thursday, April 25st 2024
8:00a - 8:45a	Arrival and Breakfast
8:50a - 9:00a	Opening Remarks
9:00a - 10:00a	Keynote Lecture: Patrick Breheny, MS PhD Inference for high-dimensional regression models: False discovery rates and confidence intervals
10:00a - 10:10a	Break
10:10a - 12:00a	Invited/Contributed Presentations: Invited Speaker: Neil Montgomery, PhD, Jointly assessing multiple endpoints in pilot and feasibility studies Invited Speaker: Scott Weir, PharmD, PhD, Translation of Cancer Biology Discoveries into Novel Cancer Therapeutic Agents - An Overview of the Drug Discovery and Development Process Contributed Speaker: Clayton Mansel, Hierarchical Clustering on Problem History in the National Alzheimer's Coordinating Centers Database Contributed Speaker: Francisco Diaz, PhD,Measuring the individualization potential of treatment individualization rules: application to rules built with a new parametric interaction model for parallel-group clinical trials
12:00a - 01:00p	Lunch Break
01:00p - 02:50p	Invited/Contributed Presentations: Invited Speaker: Bowen Liu, PhD, A summary of meta-analysis for risk factors of osteoporotic fracture Contributed Speaker: Morgan Ewald, Pleiotropic Prioritization: Unraveling Shared Genetic Threads in Insomnia and Chronic Pain Through an Advanced Gene Prioritization Pipeline Contributed Speaker: Kun Fan, Robust Sparse Bayesian Regression for Longitudinal Gene-Environment Interactions Contributed Presentations: Md Tamzid Islam, Gene network detection for glioblastoma-related multi-phase outcome prediction using an integrative machine-learning approach
03:00p - 04:30p	Poster Session and Mixer
Day 2 Program
Friday, April 26th 2024
08:00a - 09:00a	Arrival and Breakfast
09:00a - 12:00a	Short Course:Practical Dose Finding and Dose Optimization Designs in Oncology Clinical Trials Speaker: Yuan Ji, PhD
12:00p - 01:00p	Lunch
01:00p - 02:50p	Invited/Contributed Presentations: Invited Speaker: Mike Anderson, PhD, A Novel Bayesian Approach to Differential Gene Detection in Subjects with Neurocysticercosis (NCC) Associated Epilepsy Special Session for Kansas Department of Health and Environment Invited Speaker: Farah S. Ahmed, MPH, PhD, Introduction to Epidemiology and Data at the Kansas Department of Health and Environment Invited Speaker: Scott Johnston, MPH, Monthly Cluster Analysis of Emergency Department Drug Overdoses in Kansas Utilizing ESSENCE Data Invited Speaker: Andrea May, MPH, Assessing Immunization Coverage in Relation to the Social Vulnerability Index in Kansas
02:50p - 03:00p	Break
03:00p - 03:50p	Invited/Contributed Presentations: Contributing Speaker: Hanxia Li, Machine Learning Predictions of Smoking Trends: Insights from the PATH Study Contributing Speaker: Lauren Yoksh, Lactate Response to Exercise in Alzheimer's Disease versus Controls: Using Linear Mixed Models to Account for Repeated Measures and for Heterogeneous Variances Contributing Speaker: Rachel Griffard, micRoclean: an R package Decontamination Pipeline for Low-Biomass Microbiome Data
03:50p - 04:00p	Closing Remarks

Poster presentations:

Presenter	Title
Mahmud, Kazi Md Farhad	A Preliminary Study on Tumor Segmentation for Triple Negative Breast Cancer in MRI
Park, Joonha	Sampling from high dimensional, multimodal Bayesian posterior using automatically tuned, tempered Hamiltonian Monte Carlo
Jayawardhana, Ananda	Mental Health and Socio-Economic Disadvantage
Mudunkotuwa Appuhamilage, Geethanjalee	Two R Shiny Apps for Innovative Clinical Trial Designs with Time-To-Event Outcomes
Park, Joonha	On Simulation-based Inference for Implicitly Defined Models
Dutta, Sreejata	Enhancing DHA Supplementation Adherence: A Bayesian Approach with Finite Mixture Models and Irregular Interim Schedules in Adaptive Trial Designs
Komladzei,Stephan	Integrative Machine Learning Approach In Detecting Gene Networks for Predicting Liver Cancer Incidence and Survival
Kim, Min-Gyu	Detecting the use of ChatGPT in university newspapers by analyzing stylistic differences with machine learning
Isom, Madeline	Noninvasive sampling for biomarker research: combining fingerprint sampling, mass spectrometry, and machine learning
Chua, Aleesa	Evaluating Storage Conditions for the Analysis of Extracted Lipids from Latent Fingerprints Using Supervised and Unsupervised Classification
Amponsah, Jonah	Optimizing Clinical Predictions: A Patient-Centric Machine Learning (PCML) Approach
Mei, Xiaohang	A High-Dimensional Latent Regression Item Response Model for Psychometric-Neuroimaging Association Studies
Rahman, Md Atikur	Preventing data Privacy in High-dimensional multimodal and multicenter learning with ADMM-based Federated Learning
Rahman, Mohammod Mahmudur	Statistical Comparison of Two Correlated Survival Curves: An ROC-based Framework
Ahmmed, Foyez	Quantifying the complementary value of biomarkers: a framework aiming for improved combinations
Ige, Oluwatobiloba	A preliminary investigation on the effectiveness of delta radiomics for locoregional recurrence prediction in HNSCC
Pepper, Sam	Leveraging a RAG empowered LLM for Natural Language Processing on ClinicalTrials.gov
Shi, Xiaosong	Improved Mortality Analysis in Early-Phase Dose-Ranging Clinical Trials for Emergency Medical Diseases Using Bayesian Time-to-Event Models with Active Comparators
Akhter, Murshalina	Navigating the genomic landscape of Lung Cancer: Identifying prognostic Genes and Network structures using a Novel Machine Learning Approach
Chen, Xi	Explainable AI predicting Alzheimer's Disease with Multimodal Deep Neural Networks
Chen, Xi	A preliminary study on predicting pathological complete response to neoadjuvant chemotherapy in Triple-Negative Breast Cancer
Ige, Oluwatobiloba	Automated Multi-objective Model for Thrombotic and Bleeding Risk Prediction in End Stage Kidney Disease (ESKD)
Saif, Md Saiful Islam	Evaluating Pre- and Post-Treatment Cytokine Profiles for Predicting Anti-PD1 Immunotherapy Response in Head and Neck Cancer Patients
Yeboah, Kwame	A comparison study in deep learning based pathological plaque detection
Bukenya, Carolyne	Pre- and Post-COVID19 Shifts in Cancer Screening Behaviors and Risk Factors Among Patients in Kansas and Missouri
Bristi, Piali Dey	Factors Related to Recovery after Extracorporeal Life Support and Cardiogenic Shock