Yi Zheng

FourierMIL uses Fourier filtering and multiple instance learning to analyze whole-slide images, outperforming existing methods in tumor classification.

This paper develops a graph attention-based framework that fuses pathology images and gene expression data to predict cancer survival, showing improved performance over existing methods.

This paper introduces GRAPE-Net, a graph-based model that stratifies bronchial premalignant lesions using histopathology images, showing improved classification accuracy for lung cancer subtypes.