Table S6 from Interaction between Molecular Subtypes and Stromal Immune Infiltration before and after Treatment in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy
Tumor-draining lymph node (TDLN) invasion by metastatic cells in breast cancer correlates with poor prognosis and is associated with local immunosuppression, which can be partly mediated by regulatory
Image data and trained deep learning models to segment the epithelium / Ki67 positive or negative nuclei in haematoxylin/DAB immunohistochemistry images. As described in our manuscript entitled: Devel
The data and code are supplementary to the research titled: "A Self-Interpretable Deep Learning Network for Early Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy Based on Breast
We report the ability of a gene expression signature to predict response to neoadjuvant chemotherapy in early breast cancer, and also describe transcriptomic changes during treatment Overall design: T
Immune-related processes are important in underpinning the properties of clinical traits such as prognosis and drug response in cancer. The possibility to extract knowledge learned by artificial neura
