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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
HHS · no agency ID · record R0923

Medical Text Indexer-NeXt Generation (MTIX) MEDLINE Indexing

Department of Health and Human Services · HHS/NIH

Overview

Development stage
DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation
Not high-impactSource: c) Not high-impact
Impact justification
Not reported
Start date
2023-05 (month precision)Source: May-23
Withheld from public reporting
NoSource: a) No

Mission

Topic area
Administrative Functions
Operational functions
No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Time-consuming and burdensome manual indexing of MEDLINE citations

Expected benefits

Cost-effective, timely, and efficient indexing of MEDLINE citation records.

System outputs

A set of MeSH terms describing the article topic

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
Yes
Public source code
Not reported

Sourcing

How it was built
Developed in-houseSource: b) Developed in-house
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
No
Privacy Impact Assessment
Not reported
Authorization to Operate
No
Demographic features
k) None of the above
Training and evaluation data
The MTIX dataset is approximately 10 million PubMed MEDLINE citations published after 2006. It is publicly available data, used for training and evaluation of the MeSH terms predicted by the algorithm.
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