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Updated: Sep 24, 2025
05:47
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
607
Artificial intelligence in COVID-19 evidence syntheses was underutilized, but impactful: a methodological study
Juan R Tercero-Hidalgo1, Khalid S Khan2, Aurora Bueno-Cavanillas1
1Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain; CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain; Instituto Biosanitario Granada (IBS-Granada), Granada, Spain.
Journal of Clinical Epidemiology
|May 5, 2022
Summary
Artificial intelligence (AI) was underutilized in COVID-19 systematic reviews, but its use streamlined literature screening and increased publication impact. Further application of AI in systematic reviews is recommended for efficiency.
Area of Science:
- Medical Informatics
- Evidence Synthesis
- Public Health
Background:
- The COVID-19 pandemic necessitated rapid, high-quality systematic reviews.
- Artificial intelligence (AI) offers potential for automating evidence synthesis.
Purpose of the Study:
- To evaluate the application and impact of AI tools in COVID-19 systematic reviews.
- To compare AI-assisted reviews with traditional methods.
Main Methods:
- Systematic reviews of COVID-19 literature were identified and screened for AI tool usage.
- AI-utilizing reviews were compared to matched controls based on journal impact factor, screening workload, completion time, and methodological quality (AMSTAR-2).
Main Results:
- Only 0.7% of COVID-19 systematic reviews utilized AI.
- AI reviews were published in higher impact journals and involved more efficient abstract screening.
- No significant differences were observed in citation counts, full-text screening, or review completion times.
Conclusions:
- AI is an underutilized tool in systematic reviews, offering benefits in efficiency and publication impact.
- There is significant potential for AI to automate and enhance systematic review processes.
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