AI use-case explorer
AI use cases
Search and filter every reported use case. Open a record for the agency's full description, governance answers and source provenance.
Columns (7)
| Use case | Agency | Stage | High-impact | Topic area | AI classification | Sourcing |
|---|---|---|---|---|---|---|
| AHRQ Search R0622 · HHS/AHRQ/CQuIPS | HHS | Deployed | Not high-impact | Information Technology | Classical / predictive ML | Contract and in-house |
| Short-term Forecasting of Severe Outcomes for Seasonal and Epidemic Pathogens R0655 · HHS/CDC | HHS | Deployed | Not high-impact | Emergency Management | Classical / predictive ML | Contract and in-house |
| Risk Assessment Module (RAM) for the National Diabetes Prevention Program (National DPP) Operations Center. R0678 · HHS/CDC | HHS | Deployed | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| Sequential Coverage Algorithm (SCA) and partial Expectation-Maximization (EM) estimation in Record Linkage R0680 · HHS/CDC | HHS | Deployed | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Nowcasting Burden and Infection Trends for Seasonal and Epidemic Pathogens R0688 · HHS/CDC | HHS | Deployed | Not high-impact | Emergency Management | Classical / predictive ML | Contract and in-house |
| AI-assisted comment triaging tool R0740 · HHS/CMS/CM | HHS | Deployed | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| Renamed: 356H Machine Learning (ML) Facility Supply Chain Role Classification
Previously: 356H ML Facility Supply Chain Role Classification R0816 · HHS/FDA/CDER | HHS | Deployed | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Renamed: Risk-based FAR Review & Decision Support
Previously: Field Alert Reports (FAR) Prioritization Model R0817 · HHS/FDA/CDER | HHS | Deployed | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Resource Capacity Planning R0832 · HHS/FDA/CDER | HHS | Deployed | Not high-impact | Other | Classical / predictive ML | Contract and in-house |
| Warp Intelligent Learning Engine (WILEE) R0864 · HHS/FDA/HFP | HHS | Deployed | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Product Label and Text Extraction System (PLATES) R0867 · HHS/FDA/HFP | HHS | Deployed | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Machine Learning as a Service: Translate and extract text from images using AI R0876 · HHS/FDA/ODT | HHS | Deployed | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Machine Learning as a Service: Extract data from product labels, business forms, and image files R0877 · HHS/FDA/ODT | HHS | Deployed | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Filer Evaluation prioritization using risk-based decision Machine Learning approach R0878 · HHS/FDA/OII | HHS | Deployed | Not high-impact | Information Technology | Classical / predictive ML | Contract and in-house |
| ClinicalTrials.gov Protocol Registration and Results System Review Assistant R0909 · HHS/NIH | HHS | Deployed | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| DAIT AIDS-Related Research Solution R0912 · HHS/NIH | HHS | Deployed | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| Federal IT Acquisition Reform Act (FITARA) Tool R0916 · HHS/NIH | HHS | Deployed | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| Internal Referral Module (IRM) R0919 · HHS/NIH | HHS | Deployed | Presumed high-impact, determined not | Administrative Functions | Classical / predictive ML | Contract and in-house |
| Research Area Tracking Tool R0972 · HHS/NIH | HHS | Deployed | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| TB DEPOT (Tuberculosis Data Exploration Portal) R0974 · HHS/NIH | HHS | Deployed | Not high-impact | Science | Classical / predictive ML | Contract and in-house |
| GrantSolutions Recipient Risk Tool R1033 · HHS/ASFR/OG | HHS | Deployed | Not high-impact | Service Delivery | Classical / predictive ML | Contract and in-house |
| GrantSolutions Non?Competing Continuation Approval Tool R1034 · HHS/ASFR/OG | HHS | Deployed | Not high-impact | Service Delivery | Classical / predictive ML | Contract and in-house |
| Integrated Data Repository (IDR) Customer Analytic Environment (CAE) R0808 · HHS/CMS/OIT | HHS | Pilot | Not high-impact | Information Technology | Classical / predictive ML | Contract and in-house |
| Data Ingestion and Content Explorer (DICE) R0868 · HHS/FDA/HFP | HHS | Pilot | Not high-impact | Health and Medical | Classical / predictive ML | Contract and in-house |
| Person-level disambiguation for PubMed authors and NIH grant applicants R0934 · HHS/NIH | HHS | Pilot | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| Identification of emerging areas R0964 · HHS/NIH | HHS | Pilot | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
| Prediction of transformative breakthroughs R0970 · HHS/NIH | HHS | Pilot | Not high-impact | Administrative Functions | Classical / predictive ML | Contract and in-house |
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