Introduction Urine cytology offers a rapid and relatively inexpensive method to diagnose
urothelial neoplasia. In our setting of a public sector laboratory in South Africa, urothelial …

Cytology is a low-cost and non-invasive diagnostic procedure employed to support the
diagnosis of a broad range of pathologies. Cells are harvested from tissues by aspiration or …

Deep learning‐based computer vision methods have recently made remarkable
breakthroughs in the analysis and classification of cancer pathology images. However, there …

Background: Although deep learning systems (DLS) have been developed to diagnose
urine cytology, more evidences are required to prove if such systems can predict …

Abstract Evaluation of a tissue biopsy is often required for the diagnosis and prognostic
staging of a disease. Recent efforts have sought to accurately quantitate the distribution of …

Background Although deep learning algorithms for clinical cytology have recently been
developed, their application to practical assistance systems has not been achieved. In …

Background Urine cytology, although a useful screening method for urothelial carcinoma,
lacks sensitivity. As an emerging technology, artificial intelligence (AI) improved image …

Objectives To develop a classification system for urine cytology with artificial intelligence (AI)
using a convolutional neural network algorithm that classifies urine cell images as negative …

Generative adversarial networks (GANs) have received immense attention in the field of
machine learning for their potential to learn high-dimensional and real data distribution …

One of the most challenging aspects of medical image analysis is the lack of a high quantity
of annotated data. This makes it difficult for deep learning algorithms to perform well due to a …