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 …

In recent years, various AI-based methods have been developed in order to uncover
chemico-biological interactions associated with DNA damage and oxidative stress. Various …

Background Adopting a computational approach for the assessment of urine cytology
specimens has the potential to improve the efficiency, accuracy, and reliability of bladder …

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 …

Artificial neural networks (ANN), machine learning (ML), deep learning (DL), and ensemble
learning (EL) are four outstanding approaches that enable algorithms to extract information …

Objectives Cytomorphology is known to differ depending on the processing technique, and
these differences pose a problem for automated diagnosis using deep learning. We …

Artificial Intelligence (AI) is an emerging, transforming and revolutionary technology that has
captured attention worldwide. It is translating research into precision oncology treatments. AI …

Introduction: Deep learning is a subset of machine learning that has contributed to
significant changes in feature extraction and image classification and is being actively …

The assessment of polymorphonuclear leukocyte (PMN) proportions (%) of endometrial
samples is the hallmark for subclinical endometritis (SCE) diagnosis. Yet, a non-biased …

Background Intraoperative pathological diagnosis of central nervous system (CNS) tumours
is essential to planning patient management in neuro‐oncology. Frozen section slides and …