Mark Dredze Research Group

Johns Hopkins University

How can natural language processing of social media and clinical text detect and monitor public health outcomes in real time? The group develops artificial intelligence systems that apply statistical models of language to social media analysis for public health surveillance. Researchers design and evaluate statistical methods for information extraction addressing syntax, semantics, sentiment, and spoken language processing tasks. They build new clinical natural language processing methods to analyze medical records for applications in clinical informatics and medicine. Applications studied include tobacco control, vaccinations, infectious disease surveillance, mental health, drug use, and gun violence prevention using AI-based language models.