33 citations · 39 across the 2 of their papers we have counts for
3 papers
cs.CV2019
Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis
Richard J. Chen, Ming Y. Lu, Jingwen Wang +4
Cancer diagnosis, prognosis, and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data. However, mo…
cs.CV2019★ 6 cited
Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks
Jingwen Wang, Richard J. Chen, Ming Y. Lu +2
Histology-based grade classification is clinically important for many cancer types in stratifying patients distinct treatment groups. In prostate cancer, the Gleason score is a gra…
cs.CV2019★ 33 cited
Semi-Supervised Histology Classification using Deep Multiple Instance Learning and Contrastive Predictive Coding
Ming Y. Lu, Richard J. Chen, Jingwen Wang +2
Convolutional neural networks can be trained to perform histology slide classification using weak annotations with multiple instance learning (MIL). However, given the paucity of l…