Clinical
Embeds AI-enhanced medical education in real clinical workflows and measures patient outcomes. We study how simplified, personalized content changes comprehension, anxiety, and adherence at the point of care.
Communication · Understanding · Impact
Building scalable, evidence-based systems that make medical information accurate, accessible, and trusted in the digital era.
Our Mission
What we do
COMPREHEND aims to study how medical information is created, transformed, disseminated, understood, and trusted in the digital era.
By combining clinical research, AI methodology, and infodemiology, our goal is to build scalable, evidence-based systems that improve patient understanding and ensure medical information remains accurate, accessible, and impactful.
What We Study
Three lines of inquiry, one shared question
How does medical information actually reach the patients it is meant to serve?
Infodemiology
Studies how medical information spreads across digital platforms and who controls the online medical-education ecosystem. We map the creators, channels, and incentives shaping what patients read.
Technical
Builds the computational tooling that underpins the other branches: fidelity metrics, prediction models, and AI pipelines that translate complex medical text into trustworthy, readable language.
Long-Term Impact
Where we are headed
Three commitments that shape the lab's trajectory, each rooted in our mission to make medical information understandable, trustworthy, and impactful.
Close the health literacy gap in clinical care
Develop and validate scalable AI-driven tools that transform complex medical information into accurate, accessible content for every patient, regardless of language, education level, or background, so that informed decision-making is no longer limited by how a document was written.
Map and reshape the digital medical information ecosystem
Characterize how medical content moves across modern platforms, who controls its dissemination, and how presentation influences patient trust, so that physicians, institutions, and patients have an evidence base for navigating an increasingly online medical landscape.
Establish the standard for trustworthy AI in patient-facing medicine
Build automated systems that verify the factual accuracy and content fidelity of AI-generated medical text, enabling clinical AI to be deployed safely at scale without requiring expert review of every output.
Interested in collaborating?
See our research or get in touch with the team.