Objective:

To provide a quantitative synthesis of the diagnostic performance of AI-enhanced liquid biopsy models published between 2022 and 2025.

Approach:

Key Findings:

• AI-enhanced liquid biopsy achieved a pooled AUROC of 0.924 (95% CI, 0.879–0.953).
• AI-based models demonstrated an absolute AUROC improvement of 0.025 (95% CI, 0.019–0.030) compared with conventional approaches.
• Substantial between-study heterogeneity was observed (I² = 88.8%).

Interpretation:

AI's integration into liquid biopsy enhances diagnostic signal extraction from complex circulating biomarkers, supporting its potential role in molecular diagnostics.

Limitations:

• Variability in tumor type, analyte, data preprocessing, and AI model architecture complicates comparisons.
• Many studies had small sample sizes and lacked external validation.

Conclusion:

AI-enhanced liquid biopsy shows promise in improving diagnostic accuracy, but further validation and calibration are necessary for clinical application.

Sources:

• Systematic Review Registration
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