Frederick Klauschen

TL;DR: This work proposes a general solution to the problem of understanding classification decisions by pixel-wise decomposition of nonlinear classifiers by introducing a methodology that allows to visualize the contributions of single pixels to predictions for kernel-based classifiers over Bag of Words features and for multilayered neural networks.

TL;DR: Current data on the clinical validity and utility of TILs in BC are reviewed in an effort to foster better knowledge and insight in this rapidly evolving field, and to develop a standardized methodology for visual assessment on H&E sections.

TL;DR: The hypothesis that breast cancer is immunogenic and might be targetable by immune-modulating therapies is supported and increased TIL concentration predicted response to neoadjuvant chemotherapy in all molecular subtypes assessed.

TL;DR: The functionality of Cutoff Finder is illustrated by the analysis of the gene expression of estrogen receptor and progesterone receptor in breast cancer tissues, which is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival.

TL;DR: Investigating the immunogenicity of human epidermal growth factor receptor 2 -positive and triple-negative breast cancers and immunologically relevant genes in the neoadjuvant GeparSixto trial found immunologic factors were highly significant predictors of therapy response in the trial, particularly in patients treated with Cb.