Ohio State University College of Dentistry deploys Amazon Q Business POCAA to give students instant chairside access to 9,000+ curriculum artifacts

The Ohio State University College of Dentistry deployed Large Language Models & Generative AI for Clinical Decision Support in Dental & Oral Health. As reported by dentistry.osu.edu: 9,000+ curriculum artifacts indexed.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
9,000+Curriculum Artifacts Indexed
100+Courses Covered

Source-reported figures (cited source: dentistry.osu.edu)

What The Ohio State University College of Dentistry was trying to fix

Dental students must recall and integrate knowledge from thousands of hours of lectures and clinical protocols spanning 100+ courses across basic and clinical sciences. Accessing contextually relevant, curriculum-aligned information at the point of care during clinical rotations was a significant challenge, with students forced to manually search through disparate textbooks, notes, and clinical references.

What The Ohio State University College of Dentistry deployed

The college built POCAA (Point Of Care Chairside Academic Assistant) on Amazon Q Business using a RAG-based architecture. The system was trained exclusively on the college's own Pre-Doctoral and Dental Hygiene curriculum — 9,000+ artifacts across 100+ courses including lecture recordings, presentations, and syllabi. Students query the system in natural language and receive source-attributed, faculty-vetted responses that integrate knowledge across multiple dental disciplines.

Results

POCAA is currently in pilot rollout to faculty and students, with ongoing refinement of query guardrails and a sourcing accuracy model. The system provides 24/7 availability with automated ingestion of new course materials via Canvas API integration. It also supports curriculum quality improvement by surfacing redundancies, gaps, and inconsistencies through analysis of user query patterns — a capability described as first-of-its-kind at Ohio State.

Key Takeaways

  • Training an LLM exclusively on institutional curriculum (rather than general web data) ensures source reliability and faculty-vetted accuracy, which is critical for clinical education contexts.
  • RAG architecture with citation tracking allows students to verify answers and builds confidence in AI-assisted decision-making.
  • Capturing and analyzing user queries provides a secondary benefit: continuous curriculum evaluation that helps faculty identify gaps and redundancies at scale.

Evidence for The Ohio State University College of Dentistry's Clinical Decision Support deployment

Reported outcome metrics
2 cited below
Cited source
dentistry.osu.edu
Last updated
Source link checked

Explore Related

Share:

Details

Company Size
Enterprise
Company
The Ohio State University College of Dentistry

Have a similar implementation?

Share your customer's AI results and link it to your vendor profile.

Submit a case study →