SUMMARY
Dennis L. Shung, M.D., Ph.D., is a gastroenterologist at Mayo Clinic who develops trustworthy artificial intelligence (AI) and data science tools to advance gastroenterology and hepatopancreatobiliary research and clinical care.
Dr. Shung's work focuses on building and rigorously evaluating large language model-driven systems for clinical data understanding. This includes natural language querying of electronic health records, automated extraction from radiology and procedure reports, and risk prediction for conditions such as gastrointestinal (GI) bleeding.
Dr. Shung's research emphasizes safety, transparency and human oversight. His goal is enabling scalable, reproducible discovery while laying the foundation for clinically validated decision support tools.
Focus areas
Trustworthy clinical AI and evaluation frameworks
Dr. Shung develops rigorous evaluation methods to ensure that AI systems are safe, reliable and clinically meaningful before deployment. His work focuses on benchmarking large language models in real-world clinical tasks, identifying failure modes, and establishing standards for human oversight and validation in healthcare AI.
Natural language clinical data querying and cohort discovery
Dr. Shung's research builds large language model-driven systems that allow clinicians and researchers to query complex clinical data using plain language. These tools aim to accelerate cohort identification, improve reproducibility in research and reduce technical barriers associated with traditional data-extraction methods.
Automated extraction from clinical reports
Dr. Shung designs machine learning systems to extract structured information from unstructured clinical text, including radiology and endoscopy reports. This work enables large-scale data curation for research and quality improvement, which supports more efficient and accurate analysis of clinical outcomes.
Risk prediction and clinical decision support
Dr. Shung and his team develop predictive models for gastrointestinal conditions, such as GI bleeding, with a focus on improving early risk stratification and clinical decision-making. These models are designed with careful validation and integration pathways to support future clinical use.
Responsible deployment of AI in healthcare
Dr. Shung's work addresses the broader challenges of implementing AI in clinical settings, including issues of bias, generalizability and interpretability. His research contributes to frameworks that ensure AI systems are deployed responsibly, with measurable benefit to patients and healthcare professionals.
Significance to patient care
Dr. Shung's research helps healthcare professionals make better and faster decisions using clinical data. Dr. Shung and his team build tools that can read medical records and reports, find important information, and identify patients who may be at higher risk of serious conditions, like gastrointestinal bleeding. This can help care teams act earlier and choose the right treatments. Dr. Shung's work also makes it easier for researchers to study conditions using large amounts of data, which can lead to new discoveries. All tools are carefully tested and used with human oversight to ensure they are safe and helpful for patients.
Professional highlights
- American Gastroenterological Association:
- External advisor, Governing Board, 2024-present.
- Lead, Artificial Intelligence and Digital Health Taskforce, Center for GI Innovation and Technology, 2023-present.
- Keynote speaker, Leadership Summit, 2024.
- Founding member, Artificial Intelligence Institute for Gastroenterology, American Society for Gastrointestinal Endoscopy, 2024-present.
- Associate editor, Gastroenterology, 2023-present.
- Honorary visiting scientist, Lee Kong Chian School of Medicine, Nanyang Technological University, 2022-present.
- Member, International Editorial Board, Alimentary Pharmacology and Therapeutics, 2021-present.
- Coalition for Health AI (CHAI):
- Work group lead, Clinical Decision Support tools, Generative AI Work Group, 2025-2026.
- Work group lead, Safety and Reliability, Generative AI Work Group, 2024-2025.
- Young Physician-Scientist Award, American Society for Clinical Investigation, 2025.
- Co-chair, Combined Clinical Symposium on Artificial Intelligence in Gastroenterology, Digestive Diseases Week, 2022.
- Iva Dostanic Award, Yale Department of Medicine, Yale School of Medicine, 2022.