Yerong Liu

DeSide: A unified deep learning approach for cellular decomposition of bulk tumors based on limited scRNA-seq data

DeSide uses limited scRNA-seq data to estimate cell type proportions in bulk tumor samples, outperforming existing methods and enabling patient stratification based on survival rates.

Deep learning-based Spatial Feature Extraction for Prognostic Prediction of Hepatocellular Carcinoma from Pathological Images

This study develops a deep learning method to extract spatial features from H&E images of HCC, identifying features associated with patient survival and improving prognostic stratification when combined with clinical features.