March 3, 2026Open Access

The Phases of Living Evidence Synthesis Using AI: Living Evidence Synthesis (Version 1)

Key Points

Improved efficiency and accuracy were observed in living evidence synthesis using AI tools, enhancing overall research quality.
The analysis highlighted performance metrics, achieving high accuracy, recall, and F1-scores, although precision varied between tools.
Assessment involves data extraction and risk of bias evaluation, utilizing advanced AI and semiautomated methods for optimal results.
Living evidence synthesis benefits from technology, suggesting more reliable outcomes for ongoing and future research efforts.

Abstract

AI and semiautomated tools primarily facilitate data extraction or collection and risk of bias assessment. The use of AI or semiautomated tools in LE synthesis improves efficiency, leading to high accuracy, recall, and F1-scores, while precision varies across tools.

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Cite this study

Song et al. (Tue,) studied this question.

synapsesocial.com/papers/69a75b6dc6e9836116a22b96 — DOI: https://doi.org/10.2196/76130

Authors

Xuping Song

Lanzhou University of Technology

Zhenjie Lian

Lanzhou University of Technology

Rui Wang

Lanzhou University of Technology

Journals

SHILAP Revista de lepidopterología

Journal of Medical Internet Research

Actions

Institutions

McMaster University

University of Hong Kong

Lanzhou University

References and Citations

Connected Papers

Building similarity graph...

Analyzing shared references across papers

The Phases of Living Evidence Synthesis Using AI: Living Evidence Synthesis (Version 1)

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Cite this study

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion