Context Computational pathology is a new interdisciplinary field that combines traditional
pathology with modern technologies such as digital imaging and machine learning to better …

Deep learning (DL) and convolutional neural networks (CNNs) have achieved state-of-the-
art performance in many medical image analysis tasks. Histopathological images contain …

Cancer detection poses a significant challenge for researchers and clinical experts due to its
status as the leading cause of global mortality. Early detection is crucial, but traditional …

Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is
rapidly increasing due to many factors, such as unhealthy lifestyles, water and food …

Clear cell renal cell carcinoma (ccRCC) represents the most frequent form of renal cell
carcinoma (RCC), and accurate International Society of Urological Pathology (ISUP) grading …

Nanotechnology and photonics, two of the most promising fields of the 21st century, come
together in nanophotonics. Its primary advantage is that it may be used to build a number of …

Simple Summary This study included 227 patients, among whom 27.7%(63/227) were
diagnosed with tumors spread through air spaces (STASs), which have been shown to be …

This paper presents a deep learning (DL) approach for predicting survival probabilities of
renal cancer patients based solely on preoperative CT imaging. The proposed approach …

Purpose With the recent rising interest in artificial intelligence (AI) in medicine, many studies
have explored the potential and usefulness of AI in urological diseases. This study aimed to …

Deep learning (DL) has proven itself as a powerful tool to capture patterns that human eyes
may not be able to perceive when looking at high-dimensional data such as radiological …