Dr. Dillon Pruett is an Assistant Professor in the School of Communication Science and Disorders whose research bridges clinical informatics, statistical genomics, and artificial intelligence in the study of the neurobiological underpinnings of stuttering and related conditions. He leverages machine learning and natural language processing approaches to mine electronic health records (EHRs) and utilizes biobank datasets to map the genetic risk architecture of stuttering. Expanding on these computational frameworks, Dr. Pruett's current research explores agentic AI systems to autonomously navigate EHRs.
Research Areas
Publications
- "Identifying Developmental Stuttering and Associated Comorbidities in Electronic Health Records and Creating a Phenome Risk Classifier", Journal of Fluency Disorders, Jun-21, [Visit Publication]
- "Phenome Risk Classification Enables Phenotypic Imputation and Gene Discovery in Developmental Stuttering", The American Journal of Human Genetics, Dec-21, [Visit Publication]