Deep learning and machine learning in image-based hepatocellular carcinoma detection: a systematic review and meta-analysis.
AI-powered imaging improves liver cancer detection, addressing a major gap in current ultrasound surveillance of cirrhotic patients.
This SR+MA summarizes AI model performance across modalities (CT, MRI, ultrasound) for hepatocellular carcinoma detection, providing the most current pooled accuracy estimates for DL and ML approaches. Given HCC's rising incidence and the known limitations of ultrasound surveillance in cirrhosis, AI-assisted imaging represents a clinical priority for improving early detection in at-risk populations.
What the study was
- Study design
- Systematic review and meta-analysis
- Category
- Diagnostics
- Maturity
- Validated
- Journal
- Abdom Radiol (NY)
Why it surfaced
HCC is a rapidly growing liver cancer burden worldwide; AI in HCC detection is an active watchlist topic; SR+MA design provides evidence synthesis.
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