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Cochrane Evaluation of (Semi-) Automated Review Methods (CESAR): Protocol for an adaptive platform study within reviews

delete2026-06-19
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OA
AI
G
Gerald Gartlehner *
S
Susan Banda
M
Max Callaghan
J
Jo‐Ana D. Chase
A
Andreea Dobrescu
A
Angelika Eisele‐Metzger
E
Ella Flemyng
S
Sean Gardner
U
Ursula Griebler
B
Bartosz Helfer
P
Pawel Jemiolo
B
Biljana Macura
J
Jan C. Minx
A
Anna Noel-Storr
N
Noosheen Rajabzadeh Tahmasebi
A
Amin Sharifan
J
Joerg J Meerpohl
J
James Thomas
DOI:10.1016/j.jclinepi.2026.112390delete
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Abstract

Abstract

En 中文
• When applied responsibly, artificial intelligence (AI) offers the potential to enhance the efficiency of evidence synthesis while reducing the risk of human errors. • Providers of evidence-synthesis software and start-ups have integrated AI technologies to support review teams for various tasks of the review process. • Assessing the performance and usability of AI tools for evidence synthesis is challenging. • The rapid pace of AI development requires novel methodological approaches that enable comparative evaluation of AI tools under real-world conditions of evidence synthesis.
Keywords:
Study protocol
evidence synthesis
artificial intelligence
workflow validation
study within reviews

Journal

Journal of Clinical Epidemiology cover
Journal of Clinical Epidemiology
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