DAIT AIDS-Related Research Solution
Description
DAIT POs need to identify grant applications that involve AIDS-related research (ARR) so they can evaluate them for additional funding.
Detailed example
This application extracts text from grant applications as input, and then uses classification models to predict the priority and category of each grant application as the output. The output is shared along with other grant application metadata in a custom module.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
DAIT ARR suggests prioritization of grant applications that are likely to include AIDS-Related Research to assist POs in prioritizing which grants to select, which improved the review time and quality of review for ARR applications.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
A dataset was curated to train the model and is evaluated manually by user input.