With the development of artificial intelligence technology and computer hardware functions,
deep learning algorithms have become a powerful auxiliary tool for medical image analysis …

Ensuring diagnostic performance of artificial intelligence (AI) before introduction into clinical
practice is essential. Growing numbers of studies using AI for digital pathology have been …

Background Deep learning has revolutionized digital pathology, allowing automatic analysis
of hematoxylin and eosin (H&E) stained whole slide images (WSIs) for diverse tasks. WSIs …

Molecular subtypes of breast cancer are important references to personalized clinical
treatment. For cost and labor savings, only one of the patient's paraffin blocks is usually …

Recently, attention-based multiple instance learning (MIL) methods have received more
concentration in histopathology whole slide image (WSI) applications. However, existing …

Colorectal cancer (CRC) is the third most common and second most lethal cancer globally. It
is highly heterogeneous with different clinical-pathological characteristics, prognostic status …

Multiple instance learning (MIL) has recently become a powerful tool to solve the weakly
supervised classification problem on whole slide image (WSI) pathological diagnosis …

Background The emergence of digital whole slide image (WSI) has driven the development
of computational pathology. However, obtaining patch-level annotations is challenging and …

Background: Histological examination of tumor draining lymph nodes (LNs) plays a vital role
in cancer staging and prognostication. However, as soon as a LN is classed as metastasis …

Recently, multiple instance learning (MIL) has been successfully used in weakly supervised
breast cancer classification on whole‐slide imaging (WSI) and has become an important …