Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier
application and the future development trend of precision neuroscience. This review aimed …

Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …

Histopathology plays a critical role in the diagnosis and surgical management of cancer.
However, access to histopathology services, especially frozen section pathology during …

Background: Among all the cancers known today, prostate cancer is one of the most
commonly diagnosed in men. With modern advances in medicine, its mortality has been …

Variations in color and texture of histopathology images are caused by differences in
staining conditions and imaging devices between hospitals. These biases decrease the …

In the realm of medical imaging, the training of machine learning models necessitates a
large and varied training dataset to ensure robustness and interoperability. However …

Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …

Data augmentation involves artificially expanding a dataset by applying various
transformations to the existing data. Recent developments in deep learning have advanced …

Deep learning is revolutionising pathology, offering novel opportunities in disease prognosis
and personalised treatment. Historically, stain normalisation has been a crucial …

Introduction Perihilar cholangiocarcinoma (PHCC) is a rare malignancy with limited survival
prediction accuracy. Artificial intelligence (AI) and digital pathology advancements have …