Spatial transcriptomics is a newly emerging field that enables high‐throughput investigation
of the spatial localization of transcripts and related analyses in various applications for …

Androgen deprivation therapy has a central role in the treatment of advanced prostate
cancer, often causing initial tumour remission before increasing independence from signal …

In recent years, the explosive growth of spatial technologies has enabled the
characterization of spatial heterogeneity of tissue architectures. Compared to traditional …

Deep learning (DL), often called artificial intelligence (AI), has been increasingly used in
Pathology thanks to the use of scanners to digitize slides which allow us to visualize them on …

In common medical procedures, the time-consuming and expensive nature of obtaining test
results plagues doctors and patients. Digital pathology research allows using computational …

Spatially resolved transcriptomics (SRT) has evolved rapidly through various technologies,
enabling scientists to investigate both morphological contexts and gene expression profiling …

Automatic segmentation of histopathology whole-slide images (WSI) usually involves
supervised training of deep learning models with pixel-level labels to classify each pixel of …

Background and objectives Spatially resolved techniques for exploring the molecular
landscape of tissue samples, such as spatial transcriptomics, often result in millions of data …

Plant pathogens can decimate crops and render the local cultivation of a species
unprofitable. In extreme cases this has caused famine and economic collapse. Timing is vital …

Spatially resolved transcriptomics (SRT) is a pioneering method for simultaneously studying
morphological contexts and gene expression at single-cell precision. Data emerging from …