School LLM initial abstract review process
Description
Manual review and categorization of thousands of research abstracts related to school readiness science is time-consuming. The AI enables efficient extraction and categorization of themes, reducing human effort and time.
Detailed example
The AI uses an LLM to extract data from abstract reviews and categorize relevant themes and topics into a user-friendly dashboard, enabling users to pull resources from 2012–2022 for specific school closure outcomes or themes.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
The AI allows for efficient categorization of thousands of abstracts in a much shorter time frame, with less human effort, and presents results in a user-friendly dashboard for health scientists to use in research and decision-making.
Controls / human review
ATO: No; PIA: Not published