Hepatocellular carcinoma (HCC) is a major cause of cancer mortality, and understanding micronecrosis can improve prognosis predictions for patient survival post-surgery.
The researchers developed a deep learning model using Graph Convolutional Neural Networks (GCN) to analyze micronecrosis data from 3,622 tissue slides, enhancing the accuracy of prognostic predictions compared to traditional methods.
This model not only improves prognostic clarity for HCC survival but also sets a framework for integrating other pathological markers in future studies.