HHS · no agency ID · record R1009

Determining how federal pain resarch has responded to the Federal Pain Research Strategy.

Department of Health and Human Services · HHS/NIH

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The IPRCC has asked NIH to evaluate if all FPRS priorities are being addressed by NIH research. The task would require staff to categorize over 6000 grants into up to 13 FPRS priority areas. A single staff member can curate 5 grants per hour using these parameters, and agreement among staff members is approximately 30%. Therefore, we are carrying out this project using ML to be able to complete the project in a timely manner and without the need of significant staff time investment. It will identify areas of research that require staff to investigate further, instead of having staff curate the whole portfolio.

Expected benefits

Allow staff to complete the analysis requested by the IPRCC without the need for grant by grant curation of the entire Federal Pain Research Portfolio

System outputs

Expected outpus is a csv file that lists all Federally funded pain research grants and assigns them probabliltiies of addressing each of the 13 FPRS prioritites.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported