What type of study is this?

This is a Systematic Review study.

December 6, 2025Social Science Computer ReviewOpen Access

Evaluating the AI Tool “Elicit” as a Semi-Automated Second Reviewer for Data Extraction in Systematic Reviews: A Proof-of-Concept

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Elicit achieved 81.4% accuracy in data extraction from systematic reviews, closely matching human reviewers' 86.7% accuracy.
Comparison involved 43 studies with 602 data points to evaluate Elicit's extraction against a consensus-based ground truth.
Systematic reviews benefit from semi-automated processes, leveraging AI to support workload reduction while maintaining data integrity.
Using Elicit as a second reviewer may enhance reliability in data extraction, particularly under resource constraints.

Authors

JFJakob Fink‐LamotteUniversity of Potsdam

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Implication

Proof-of-concept study shows Elicit's data extraction performance is reliable for systematic reviews, ensuring good data quality in dermatology research.

Cite This Study

Jakob Fink‐Lamotte (2025) studied this question.

synapsesocial.com/papers/69337d09b3f947a0a125ab30 https://doi.org/10.1177/08944393251404052

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Implication

Proof-of-concept study shows Elicit's data extraction performance is reliable for systematic reviews, ensuring good data quality in dermatology research.

Evaluating the AI Tool “Elicit” as a Semi-Automated Second Reviewer for Data Extraction in Systematic Reviews: A Proof-of-Concept

Key Points

Discussion

Implication

Cite This Study

Evaluating the AI Tool “Elicit” as a Semi-Automated Second Reviewer for Data Extraction in Systematic Reviews: A Proof-of-Concept

Key Points

Discussion

Implication

Cite This Study

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