… cytology image analysis to investigate the advanced methods and comprehensive applications.
We first introduce various deep learning … research directions of computational cytology. …

… intelligence (AI) and deep learning in pathology, including cytopathology. However, there
are … discusses cytology-specific challenges, including the need to implement digital cytology …

Deep learning (DL) is a component or subset of artificial intelligence. DL has contributed
significant change in feature extraction and image classification. Various algorithmic models …

… Automated scanning and deep-learning evaluation of DS slides can improve throughput, …
of DS cytology slides. Cloud-based evaluation provides ample computational capacity and …

… Liquid-based cytology (LBC) is currently more widely used … It is crucial to develop new
computational techniques to … [10] suggested a similar method that makes use of a deep learning …

… Medical ethics: The patient's data will used for the deep learning in the computational
cytology. The volume of the data is large and therefore to maintain high level confidentiality is a …

… need for innovative computational pathology tools that will … One particular type of AI algorithm,
called deep learning, has … domain, deep learning represents a computational pathology …

… computational cytology, which combines next generation AI with digital whole slide imaging
cytology. … be curated and used to better train algorithms, as well as deep learning AI models …

… computational cost of employing computational techniques. For practical clinical usage, we
develop a fast, efficient, and fully automatic deep learning … that the proposed deep learning …

… The motivation of this article is to give a comprehensive overview of deep learning in
cervical cytopathology image analysis as well as popular deep learning techniques, and their …