Computational cytology is a critical, rapid-developing, yet challenging topic in medical
image computing concerned with analyzing digitized cytology images by computer-aided …

Artificial intelligence is highly regarded as the most promising future technology that will
have a great impact on healthcare across all specialties. Its subsets, machine learning, deep …

Bladder cancer (BCa) is the most common malignancy of the urinary tract and the most
expensive malignancy to treat over the patients' lifetime. In recent years a number of studies …

Cytopathological examination plays a crucial role in cancer diagnosis as it reflects the
cellular pathology of cancer. However, this process traditionally relies on the visual …

Simple Summary Artificial intelligence (AI) has attracted significant interest in the healthcare
sector due to its promising results. Cytological examination is a critical step in the initial …

Background The Paris System for Reporting Urinary Cytology (TPS) has been shown to
improve bladder cancer diagnosis. Advances in artificial intelligence (AI) may assist and …

Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology
laboratory. However, peer reviewed real-world data and literature are lacking in regard to …

Background Urine cytology is generally considered the primary approach for screening for
recurrence of bladder cancer. However, it is currently unclear how best to use cytological …

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 …

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