A novel method is developed for predicting the stage of a cancer tissue based on the
consistency level between the co-expression patterns in the given sample and samples in a …

Despite great advances, molecular cancer pathology is often limited to the use of a small
number of biomarkers rather than the whole transcriptome, partly due to computational …

Elucidating the molecular basis of human cancers is an extremely complex and challenging
task. A wide variety of computational tools and experimental techniques have been used to …

Prostate cancer is a serious genetic disease known to be one of the most widespread
cancers in men, yet the molecular changes that drive its progression are not fully …

Molecular subtyping of cancer is recognized as a critical and challenging step towards
individualized therapy. Most existing computational methods solve this problem via multi …

Accurate cancer detection and diagnosis is of utmost importance for reliable drug-response
prediction. Successful cancer characterization relies on both genetic analysis and …

Histopathology is considered the gold standard in determining the presence and nature of
tumors. Technological advances in automated high-speed and high-resolution wholeslide …

Cancer histology reflects underlying molecular processes and disease progression and
contains rich phenotypic information that is predictive of patient outcomes. In this study, we …

Determining the dynamics of pathways associated with cancer progression is critical for
understanding the etiology of diseases. Advances in biological technology have facilitated …

While computational methods have made substantial progress in improving the accuracy
and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction …