SDSS2026
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Lightning

CS009 Lightning Session 1, Part 1

Wed, Apr 29, 1:15 PM - 2:45 PM Room Milwaukee A Hyatt Regency Milwaukee
Sarah KalicinChair
Data Science ApplicationsAI and LLM Applications

About this session

This session will be followed by an e-poster session on April 29 from 2:45 - 3:10 PM.

14 Presentations

A RAG-based Classification Tool for Automating and Standardising Competency Mapping in Public Service
1:15 PM - 2:45 PM
Co-authors: Zhihan Chen, Lian Ping Ler (Ministry of Manpower)
Large Language Models (LLM)Retrieval-Augmented Generation (RAG)Automated Classification
AI Agents to Enhance Difficult Conversations Among Nursing Students
1:15 PM - 2:45 PM
Co-authors: Hiba Armaghan, Rachel Malander (Creighton University), Hiba Armaghan, Lindsay Iverson (Creighton University), Tamara Oliver (Creighton University), Amanda Kirkpatrick (Creighton University), Steven Fernandes (Creighton University)
AI Agents
AI Enhanced Clinical Pharmacology: Building Smarter Prescribers Through Interactive, Lifespan Centered Learning
1:15 PM - 2:45 PM
Co-authors: Erika Germinario, Erika Germinario, Ashlyn Viereck (Creighton University), Seamus Gerner, Lindsay Iverson (Creighton University), Steven Fernandes (Creighton University)
AI Enhanced Clinical Pharmacology
Application of Generative AI to Suicidal Ideation on Social Media
1:15 PM - 2:45 PM
Co-authors: Sophia Yuan (Parkview High School), Sophia Yuan (Parkview High School)
Generative AISuicidal IdeationTwitter
Evaluating Single-Agent and Multi-Agent AI Architectures for Analytical Modeling
1:15 PM - 2:45 PM
Co-authors: Praveen Gupta Sanka, Praveen Gupta Sanka, Vidya Minukuri (Convergence Inc)
AI AgentsArtificial IntelligenceAnalytics WorkflowSingle Agent vs Multi Agent ArchitectureAnalytics Modeling Automation
Improving Road Intersection Classification Using Latent Network Structure
1:15 PM - 2:45 PM
Co-authors: Ramchandra Rimal (Middle Tennessee State University), Abigail Kelly (Middle Tennessee State University), Ramchandra Rimal (Middle Tennessee State University)
Generalized Random Dot Product GraphsRoad Intersection ClassificationGATMachine Learning
Longitudinal Data-Driven Prediction of Type 2 Diabetes
1:15 PM - 2:45 PM
Co-authors: Peggy Akabuah, Kristina Vatcheva (University of Texas Rio Grande Valley), Peggy Akabuah
Type 2 DiabetesLongitudinal DataMachine Learning, Mixed Effect Random Forest, Random Forest, and Extreme Gradient BoostingPredictive ModelingTraditional Modeling, Generalized Linear Mixed Model (GLMM), and Generalized Estimating EquationsUK Data Set
Machine Learning Approaches to Predict Sepsis Risk in Multiple Myeloma Patients Treated with Bispecific Antibodies
1:15 PM - 2:45 PM
Co-authors: Anand George, Anand George, Nicholas Semenkovich (Medical College of Wisconsin DSI), Aishee Bag (Rutgers Cancer Institute, New Jersey), Mansi Shah (Rutgers Cancer Institute, New Jersey,), Sabarinath Radhakrishnan (Medical College of Wisconsin), Binod Dhakal (Medical College of Wisconsin), Samer Al Hadidi (University of Arkansas for Medical Sciences, Little Rock,), Rajshekhar Chakraborty (Herbert Irving Comprehensive Cancer Center, New York,), Carolina Schinke (University of Arkansas for Medical Sciences, Little Rock,), Anita D’Souza (Medical College of Wisconsin), Aniko Szabo (Medical College of Wisconsin), Meera Mohan (Medical College of Wisconsin)
Neural NetworkSepsisMultiple MyelomaBispecific Antibodies
Measuring the Unseen: A Statistical Approach to Quantifying Narrative Bias in Historical Accounts
1:15 PM - 2:45 PM
Co-authors: Annie Nguyen, Jonathan Auerbach (George Mason University), Annie Nguyen
Text embeddingNarrative decompositionNatural Language ProcessingHuman–AI collaborationCosine distanceGenerative AI
Modeling Counts of Census Responses over a Span of Time
1:15 PM - 2:45 PM
Co-authors: Andrew Raim (U.S. Census Bureau), Andrew Raim (U.S. Census Bureau)
BayesianPoissonRegressionFinite MixtureGibbs Sampler
On-the-Fly versus Pre-Saved Data Augmentation for Deep Learning–Based Ophthalmic Image Classification
1:15 PM - 2:45 PM
Co-authors: Gifty Duah (University of Texas Rio Grande Valley), Gifty Duah (University of Texas Rio Grande Valley), Eric Nyarko (University of Ghana), Justice Effah (University of Texas Rio Grande Valley), Isaac Numoah (Old Dominion University)
Ophthalmic imagingdata augmentation and optical coherence tomography (OCT)on-the-fly augmentationpre-saved augmentationDeep Learning and retinal fundus imagesMobileNetV2 and medical image classification.
Reproducible Extraction of Drug–Event Latency From Pharmacovigilance Narratives Using Large Language Models and Statistical Monitoring
1:15 PM - 2:45 PM
Co-authors: Swarnita Chakraborty (Johnson & Johnson), Swarnita Chakraborty (Johnson & Johnson), Geoffrey Gipson (Johnson & Johnson), Yauheniya Cherkas (Johnson & Johnson), Ricardo Vale de Andrade (Johnson & Johnson), Joao Barbosa (Johnson & Johnson), Zainab Aziz Zaveri (Johnson & Johnson), Hien Bui (Johnson & Johnson), Mark Oliver Amponin (Johnson & Johnson)
Large language models (LLMs)Generative AIPharmacovigilance and Safety AnalyticsLatency EstimationReproducibilityStatistical Monitoring
Quantifying Intersectional Bias in Clinical Foundation Models: A Counterfactual Digital Twin Audit
1:15 PM - 2:45 PM
Co-authors: Shuimei Liu (China University of Political Law and Science), Lei Guo (VA St. Louis HealthCare System), Lei Guo (VA St. Louis HealthCare System)
Counterfactual AuditAlgorithmic AuditingIntersectional Bias
AI as a Teaching Tool for Tonsillolith Detection
1:15 PM - 2:45 PM
Co-authors: Seamus Gerner, Danielle Carroll (Creighton University), Seamus Gerner, Niranzena Panneer Selvam (Instructor), Steven Fernandes (Creighton University)
AI as a Teaching ToolTonsillolith Detection
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