The emerging role of deep learning in 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 are used in DL such as a convolutional neural network (CNN), recurrent neural network, restricted Boltzmann machine, deep belief network and autoencoders. Of these, CNN is the most commonly used algorithm in the field of pathology for feature extraction and building neural network models. DL may be useful for tumour diagnosis, classification of the tumour and grading of the tumour in cytology. In this brief review, the basic concept of the DL and CNN are described. The application, prospects and challenges of the DL in the cytology are also discussed.