Working Group Webinar Library

The VaxHesSTL framework combines Graph and Recurrent Neural Networks to predict vaccine hesitancy at the ZIP code level by capturing both spatial relationships and historical trends, outperforming existing models when trained on a six-year, five-million-person insurance claims dataset from Virginia. To address the high cost of such data, the research also explores an active learning approach to optimize which ZIP codes are selected for training.

Explore an AI-driven framework that improves EHR note comprehension and promotes patient empowerment through enhanced health literacy, medical jargon translation, and support for positive behavioral change.

Nursing education is already using AI, but are we teaching it intentionally, ethically, and effectively? Join informatics leaders and interdisciplinary experts as we explore AI competencies, real teaching examples, and what AACN should consider next. Watch the Webinar Presenters

As machine learning continues to revolutionize various scientific domains, its impact on epidemic time series forecasting has become increasingly significant. This talk examines how advanced machine learning methods can address several pressing challenges in epidemic forecasting, including capturing spatiotemporal disease dynamics, coping with limited data, and developing scalable tools for research and deployment. I will first present a graph neural ODE framework for modeling the continuous spread of infectious diseases across regions. I will then show how pretraining on large-scale epidemic data can improve forecasting accuracy and enhance generalization across heterogeneous outbreak settings. Finally, I will introduce EpiLearn, our modular open-source Python toolkit for machine learning in epidemic modeling, which supports forecasting and source detection through unified pipelines for datasets, transformations, simulation, benchmarking, and visualization. I will conclude by highlighting several promising directions for future research in machine learning for epidemic forecasting. Presenter

After two decades in NLP research, Wendy Chapman explores why she pivoted toward real-world clinical impact and the challenges of implementing AI in health care.