The emerging role of deep learning in cytology

다국어 초록 (Multilingual Abstract)

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.
Deep learning is a subset of artificial intelligence. In this review, the basic concepts of deep learning and convolutional neural networks are explained. The potential applications and challenges of deep learning in cytology are discussed.