Cathy Shyr

Biography
Cathy Shyr is an assistant professor of biomedical informatics, pediatrics, and biostatistics at Vanderbilt University Medical Center. She received her PhD in biostatistics from Harvard University and is a statistical informatician specializing in machine learning (ML), AI, and causal inference methods for estimating personalized treatment effects. Her research focuses on the development and implementation of novel statistical ML and AI methods to advance precision medicine. Dr. Shyr leads the AI initiatives at the Vanderbilt Undiagnosed Diseases Network, developing and implementing large language models that leverage electronic health records data to accelerate rare disease diagnosis. She has developed methods that improve the generalizability of statistical ML and causal inference models across multiple heterogeneous datasets for estimating personalized risks and treatment effects. She is an active member of the All of Us Research Programs Data and Research Center, where she leads the development of AI tools supporting the return of study results.

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Talk
Accelerating Rare Disease Diagnosis with Artificial Intelligence
This showcase highlights AI and statistical machine learning methods developed using real-world rare disease patient data at the Vanderbilt Undiagnosed Diseases Network to improve diagnostic accuracy and efficiency. These tools provide a scalable, reproducible framework for accelerating diagnoses for health systems evaluating undiagnosed patients with complex and rare conditions.

AI for Clinical Decision Support Systems Showcase:
Vanderbilt University Medical Center
Vanderbilt University Medical Center (VUMC) is a leading academic medical center and research institution known for its nationally recognized clinical programs, biomedical innovation, and translational science. VUMC integrates patient care, research, and education to advance precision medicine and improve health outcomes.