Background Breast cancer is a highly heterogeneous disease that comprises multiple
biological components. Owing its diversity, patients have different prognostic outcomes; …

Cancer subtyping delivers valuable insights into the study of cancer heterogeneity and
fulfills an essential step toward personalized medicine. For example, studies in breast …

With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference
between various subtypes, so as to infer the underlying mechanisms. Given the available …

Classification of breast cancer subtypes using multi-omics profiles is a difficult problem since
the data sets are high-dimensional and highly correlated. Deep neural network (DNN) …

Breast Cancer comprises multiple subtypes implicated in prognosis. Existing stratification
methods rely on the expression quantification of small gene sets. Next Generation …

Abstract Background and objective Deep Learning models have emerged as a significant
tool in generating efficient solutions for complex problems including cancer detection, as …

Background Breast cancer is a collection of multiple tissue pathologies, each with a distinct
molecular signature that correlates with patient prognosis and response to therapy …

Background. Breast invasive carcinoma (BRCA) is not a single disease as each subtype has
a distinct morphology structure. Although several computational methods have been …

Accurately determining the molecular subtypes of breast cancer is important for the
prognosis of breast cancer patients and can guide treatment selection. In this study, we …

Background Classifying breast cancer subtypes is crucial for clinical diagnosis and
treatment. However, the early symptoms of breast cancer may not be apparent. Rapid …