Innovations in Design Analysis and Dissemination (IDAD): Frontiers in Biostatistics & Data Science
IDAD - Meeting Registration
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IDAD - Meeting Registration
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
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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:
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12:00a - 01:00p | Lunch Break |
01:00p - 02:50p | Invited/Contributed Presentations:
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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
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12:00p - 01:00p | Lunch |
01:00p - 02:50p | Invited/Contributed Presentations:
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02:50p - 03:00p | Break |
03:00p - 03:50p | Invited/Contributed Presentations:
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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 |
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