AI-Assisted Staging and Treatment Decision-Making for Hepatocellular Carcinoma

The precise treatment of primary hepatocellular carcinoma (HCC) highly depends on accurate disease staging (CNLC, TNM, BCLC) and scientific treatment decision-making, which necessitate the integration of both imaging and clinical baseline data. This study prospectively recruits HCC patients and clinical physicians across different hospital tiers to evaluate the clinical value of a self-developed artificial intelligence (AI) model in assisting multi-dimensional comprehensive assessment and treatment decision-making. Utilizing a Multi-Rater Multi-Case (MRMC) crossover balanced design, the study compares the accuracy of clinical evaluations performed by physicians under "unassisted (without AI)" versus "AI-assisted" conditions. A key focus is to explore whether AI can significantly enhance the comprehensive assessment capabilities of physicians in primary/secondary care hospitals, thereby prospectively reducing diagnostic and therapeutic heterogeneity across different institutional levels.