Renal cancer management is challenging from diagnosis to treatment and follow-up. In
cases of small renal masses and cystic lesions the differential diagnosis of benign or …

Context The incidental detection of localized renal masses has been rising steadily, but a
significant proportion of these tumors are benign or indolent and, in most cases, do not …

Radiomics and artificial intelligence (AI) may increase the differentiation of benign from
malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma …

Deep learning integration in cancer diagnosis enhances accuracy and diagnosis speed
which helps clinical decision-making and improves health outcomes. Despite all these …

Simple Summary Our study provides an overview of the current state of artificial intelligence
applications in urooncology and explores potential future advancements in this field. With …

Two decades since their inception, multidisciplinary teams (MDTs) are widely regarded as
the 'gold standard'of cancer care delivery. Benefits of MDT working include improved patient …

OBJECTIVE To develop and test the ability of a convolutional neural network (CNN) to
accurately identify the presence of renal cell carcinoma (RCC) on histopathology …

Radiomics texture analysis offers objective image information that could otherwise not be
obtained by radiologists′ subjective radiological interpretation. We investigated radiomics …

Simple Summary Current imaging techniques do not reliably distinguish renal cell
carcinoma from other renal diseases. This review summarizes recent advances in other …

Renal cell carcinoma is a significant health burden worldwide, necessitating accurate and
efficient diagnostic methods to guide treatment decisions. Traditional pathology practices …