Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …

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

Background Deep learning enables accurate high-resolution mapping of cells and tissue
structures that can serve as the foundation of interpretable machine-learning models for …

Abstract Tumor-Infiltrating Lymphocytes (TILs) have strong prognostic and predictive value
in breast cancer, but their visual assessment is subjective. To improve reproducibility, the …

Whole slide imaging is becoming a routine procedure in clinical diagnosis. Advanced image
analysis techniques have been developed to assist pathologists in disease diagnosis …

Recently, the use of feature attribution methods in explainable artificial intelligence has
attracted significant attention. While many proposed methods in this domain involve …

Based on text analysis, public big data management is studied. The public data
management of Mount Wutai tourism network travel notes is discussed. The positive, neutral …

Artificial intelligence (AI) systems are already being used in various healthcare areas.
Similarly, they can offer many advantages in hospital emergency services. The objective of …

Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists
grade the microscopic appearance of breast tissue using the Nottingham criteria, which is …

Background Axillary lymph node (ALN) status is a crucial prognostic indicator for breast
cancer metastasis, with manual interpretation of whole slide images (WSIs) being the current …