Abundant accumulation of digital histopathological images has led to the increased demand
for their analysis, such as computer-aided diagnosis using machine learning techniques …

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 …

Objective Over the past years, the application of artificial intelligence (AI) in medicine has
increased rapidly, especially in diagnostics, and in the near future, the role of AI in medicine …

Visual inspection of histopathology images of stained biopsy tissue by expert pathologists is
the standard method for grading of prostate cancer (PCa). However, this process is time …

Digital histology images are amenable to the application of convolutional neural networks
(CNNs) for analysis due to the sheer size of pixel data present in them. CNNs are generally …

Breast histology image classification is a crucial step in the early diagnosis of breast cancer.
In breast pathological diagnosis, Convolutional Neural Networks (CNNs) have …

Histopathology is diagnosis based on visual examination of tissue sections under a
microscope. With the growing number of digitally scanned tissue slide images, computer …

Liver cancer is a leading cause of cancer deaths worldwide due to its high morbidity and
mortality. Histopathological image analysis (HIA) is a crucial step in the early diagnosis of …

As data-driven science, artificial intelligence (AI) has paved a promising path toward an
evolving health system teeming with thrilling opportunities for precision oncology …

This study evaluates the quality of published research using artificial intelligence (AI) for
ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of …