Dextr: Automated Data Extraction Tool | National Institute of Environmental Health Sciences
Source: https://www.niehs.nih.gov/research/atniehs/labs/iha/projects/dextr
Archived: 2026-04-23 17:20
Dextr: Automated Data Extraction Tool | National Institute of Environmental Health Sciences
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Dextr: Automated Data Extraction Tool
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Project Status
The Dextr tool is operational with ongoing development.
Branches and DTT Programs
Integrative Health Assessments Branch
Scientific Cyberinfrastructure
Background information
The Division of Translational Toxicology (DTT), in partnership with ICF and Evidence Prime, developed Dextr, a web-based tool to accelerate data extraction in literature reviews. Dextr uses automated approaches, including machine learning and large language models, to: 1) identify and extract entities, like the animal model or species, and 2) enable users to then review, edit, and confirm the entries. This approach balances automation with expert oversight, providing a more efficient workflow without sacrificing transparency or accuracy.
Key Advantages:
Maintains accuracy while cutting extraction time nearly in half.
Extracts complex concepts (e.g., multiple experiments, exposures, and doses within a single study).
Links extracted elements within studies for richer, machine-readable annotated exports.
Addresses unique challenges of environmental health literature through a simple user interface.
Features:
Employs large language models, natural language processing models, and RegEx-based extraction approaches.
Supports controlled vocabularies for structured categorization.
Offers single-extractor and quality control (QC) validation modes.
Extracts data from tables.
For more information or to request access to explore the tool, email
Vickie R. Walker (
[email protected]
)
.
Documents
Walker VR, Schmitt CP, Wolfe MS, Nowak AJ, Kulesza K, Williams AR, Shin R, Cohen J, Burch D, Stout MD, Shipkowski KA, Rooney AA. 2022. Evaluation of a semi-automated data extraction tool for public health literature-based reviews: Dextr. Environ Int 159:107025. doi: 10.1016/j.envint.2021.107025. [
Abstract
]
Nowak A, Kunstman P. 2018. Team EP at TAC 2018: Automating data extraction in systematic reviews of environmental agents. Paper presented at: National Institute of Standards and Technology Text Analysis Conference. Gaithersburg, MD. [
Abstract
]
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to Top
Last Reviewed: February 06, 2026
Skip Navigation
Dextr: Automated Data Extraction Tool
Close the left navigation
Add
Project Status
The Dextr tool is operational with ongoing development.
Branches and DTT Programs
Integrative Health Assessments Branch
Scientific Cyberinfrastructure
Background information
The Division of Translational Toxicology (DTT), in partnership with ICF and Evidence Prime, developed Dextr, a web-based tool to accelerate data extraction in literature reviews. Dextr uses automated approaches, including machine learning and large language models, to: 1) identify and extract entities, like the animal model or species, and 2) enable users to then review, edit, and confirm the entries. This approach balances automation with expert oversight, providing a more efficient workflow without sacrificing transparency or accuracy.
Key Advantages:
Maintains accuracy while cutting extraction time nearly in half.
Extracts complex concepts (e.g., multiple experiments, exposures, and doses within a single study).
Links extracted elements within studies for richer, machine-readable annotated exports.
Addresses unique challenges of environmental health literature through a simple user interface.
Features:
Employs large language models, natural language processing models, and RegEx-based extraction approaches.
Supports controlled vocabularies for structured categorization.
Offers single-extractor and quality control (QC) validation modes.
Extracts data from tables.
For more information or to request access to explore the tool, email
Vickie R. Walker (
[email protected]
)
.
Documents
Walker VR, Schmitt CP, Wolfe MS, Nowak AJ, Kulesza K, Williams AR, Shin R, Cohen J, Burch D, Stout MD, Shipkowski KA, Rooney AA. 2022. Evaluation of a semi-automated data extraction tool for public health literature-based reviews: Dextr. Environ Int 159:107025. doi: 10.1016/j.envint.2021.107025. [
Abstract
]
Nowak A, Kunstman P. 2018. Team EP at TAC 2018: Automating data extraction in systematic reviews of environmental agents. Paper presented at: National Institute of Standards and Technology Text Analysis Conference. Gaithersburg, MD. [
Abstract
]
Back
to Top
Last Reviewed: February 06, 2026