Identifying pain vs non-pain research
Description
Identifying pain research studies is complicated because of the ubiquity of pain in language. NIH program staff working in the pain research field need to be able to distinguish pain research from opioid research, both of which get classified as "Pain Research" by RCDC. This usually requires significant investment of staff time, however, since a large enough training dataset has been developed we are trying to train various ML algorithms to be able to identify grants that are truly researching pain compared to grants that merely mention pain in their text.
Detailed example
Expected output is a file with a list of grants that were identified as pain related.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
It is expected that this will decrease the amount of staff time needed to curate a portfolio as starting point of analyses and that it will speed up the time it takes to carryout an analysis.
Controls / human review
ATO: Not reported; PIA: Not published