Precision oncology relies on the identification of targetable molecular alterations in tumor
tissues. In many tumor types, a limited set of molecular tests is currently part of standard …

Background Risk stratification or progression in prostate cancer is performed with the
support of clinical-pathological data such as the sum of the Gleason score and serum levels …

Contrastive visual language pretraining has emerged as a powerful method for either
training new language-aware image encoders or augmenting existing pretrained models …

Spiking neural networks (SNNs) are regarded as a promising candidate to deal with the
major challenges of current machine learning techniques, including the high energy …

Digital pathology provides a possibility for computational analysis of histological slides and
automatization of routine pathological tasks. Histological slides are very heterogeneous …

Lung diseases carry a significant burden of morbidity and mortality worldwide. The advent of
digital pathology (DP) and an increase in computational power have led to the development …

Three-dimensional excitation-emission matrix (3D-EEM) fluorescence spectroscopy has
been widely applied to detect the fluorescent components in samples from natural water …

Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …

A turbulent medium with eddies of different scales gives rise to fluctuations in the index of
refraction during the process of wave propagation, which interferes with the original spatial …

Background Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with
localized prostate cancer. However, ADT can negatively impact quality of life, and there …