AI Achieves High Accuracy in Hepatic Steatosis Detection
A 2026 systematic review and meta-analysis in Journal of Medical Internet Research evaluated 36 studies of AI diagnostic models for hepatic steatosis, finding pooled sensitivity 0.95, specificity 0.93, and AUC 0.98. The analysis identified substantial heterogeneity (I² >75%) and high patient-selection bias (44.4%), and found deep learning models outperform traditional methods. Authors recommend prospective multicenter external validation and standardized protocols to enable clinical translation.
Scoring Rationale
Strong pooled diagnostic evidence and peer-reviewed synthesis, limited by high heterogeneity and bias in included studies.
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