Background Breast cancer is the most common cancer in women worldwide, with a great
diversity in outcomes among individual patients. The ability to accurately predict a breast …

Breast cancer is a heterogeneous disease featuring distinct histological, molecular and
clinical phenotypes. Although traditional classification systems utilising clinicopathological …

Context.—The pioneering works on molecular classification (MC) by Perou and Sorlie et al
in the early 2000s using global gene expression profiling identified 5 intrinsic subtypes of …

The need for AI systems to provide explanations for their behaviour is now widely
recognised as key to their adoption. In this article, we examine the problem of trustworthy AI …

Simple Summary A deep learning model based on multi-omics data to classify Nottingham
prognostic Index score levels. The model represents each omic dataset using 2-dimensional …

Breast cancer (BC) comprises a diverse spectrum of diseases featuring distinct presentation,
morphological, biological, and clinical phenotypes. BC behaviour and response to therapy …

The use of molecular signatures to add value to standard clinical and pathological
parameters has impacted clinical practice in many cancer types, but perhaps most notably in …

Background Although many prognosis-predicting molecular scores for breast cancer have
been developed, they are applicable to only limited disease subtypes. We aimed to develop …

BACKGROUND There is uncertainty about the chemotherapy sensitivity of some oestrogen
receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast …

One of the methods for stratifying different molecular classes of breast cancer is the
Nottingham prognostic index plus, which uses breast cancer relevant biomarkers to stain …