This is a review on the use of artificial intelligence for digital breast pathology. A systematic
search on PubMed was conducted, identifying 17,324 research papers related to breast …

Pathology clinical practice has evolved by adopting technological advancements initially
regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and …

Every year, millions of women across the globe are diagnosed with breast cancer (BC), an
illness that is both common and potentially fatal. To provide effective therapy and enhance …

In clinical settings, the implementation of deep neural networks is impeded by the prevalent
problems of label scarcity and class imbalance in medical images. To mitigate the need for …

The segmentation of nuclei from histopathology images provides the necessary information
to diagnose cancer. Existing deep learning-based nuclei segmentation approaches demand …

Background and objectives Histological grade and molecular subtype have presented
valuable references in assigning personalized or precision medicine as the significant …

Abstract Background and Objective Breast cancer is one of the most common malignancies
in women, and the pathological grading of breast cancer is very important for the prognosis …

Abstract Background/Objectives: Nuclear pleomorphism, a crucial determinant of breast
cancer grading under the Nottingham Histopathology Grading (NHG) system, remains …

In accordance with the concept of game antagonism, Generative Adversarial Network (GAN)
is a popular model in current image generation technology. However, GAN has problems …

Ultrasound curve angle (UCA) measurement provides a radiation-free and reliable
evaluation for scoliosis based on ultrasound imaging. However, degraded image quality …