Artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools in the
diagnosis and treatment of bladder cancer, offering significant advancements in accuracy …

Simple Summary Non-muscle-invasive bladder cancer is associated with its high rates of
progression and recurrence, the proper diagnosis and management can save lives. Bladder …

Bladder cancer is currently the most frequent and worst cancer in the United States. Over the
last several decades, bladder cancer detection and therapy breakthroughs have significantly …

Bladder cancer is a significant health concern worldwide, necessitating effective diagnostic
and monitoring strategies. Biomarkers play a crucial role in the early detection, prognosis …

Background To reduce the mortality related to bladder cancer, efforts need to be
concentrated on early detection of the disease for more effective therapeutic intervention …

Background Applying deep learning to digital histopathology is hindered by the scarcity of
manually annotated datasets. While data augmentation can ameliorate this obstacle, its …

Introduction The objective of this systematic review is to summarize the use of machine
learning (ML) in predicting overall survival (OS) in patients with bladder cancer. Methods …

Bladder cancer (BC) remains a major disease burden in terms of incidence, morbidity,
mortality, and economic cost. Deciphering the intrinsic molecular subtypes and identification …

Everyone talks about the metaverse but few know what it really is. Augmented reality, virtual
reality, internet of things (IoT), 5G, blockchain: these are just some of the technologies …

Background Bladder cancer, a highly fatal disease, poses a significant threat to patients.
Positioned at 19q13. 2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is …