Ryan Stidham
Biological Sciences, Healthcare Research
Artificial Intelligence, Data Integration, Image Data, Machine Learning, Natural Language Processing
Relevant Projects:

NIH – Automated Bowel Segmentation of CT and MRI for Predicting Clinical Outcomes of Crohn’s disease.

Ryan Stidham

Associate Professor

Computational Medicine and Bioinformatics

Assistant Professor of Gastroenterology and Internal Medicine, Medical School

Dr. Stidham is an academic gastroenterologist specializing in medical image analysis in Crohn’s disease, ulcerative colitis, inflammatory bowel diseases (IBD), and gastroenterology conditions at large. His research is focused on developing new measures of disease activity to power automated care models and clinical decision support systems in IBD with a focus on medical image analysis and new technology development. His work has focused on automation of existing IBD disease measures that relying on colonoscopy, CT, MRI, and ultrasound using neural networks and novel image analysis approaches. Dr. Stidham is also developing new measures of disease activity, inflammation, and fibrosis that leverage advances in image segmentation, transfer learning, signals analysis, and fuzzy network approaches as well as collaborating for development of new image acquisition modalities. Finally, his team has active projects in collaboration with the Department of Learning Health Sciences for merging data from clinical office notes with imaging data using computational linguistics approaches. His work has been supported by the NIH, DOD, NSF, and several large investigator-initiated industry collaborations.