A Critical Review of Deep Learning Technique and Its Applications in Clinical Cytology

Deep learning (DL) is an emerging area of artificial intelligence and has the immense potential to reshape the field of cytology. In last few decades, there are many significant progresses in the digital pathology that includes significant increase of the computational power, data storing facilities, and whole slide imaging system. These changes have facilitated the applications of DL. DL can be used in cancer screening, disease identification and classification, predicting biomarkers, prognostic assessment, molecular data interpretation, and precision medicine. There are many obstacles to implement DL. Data collection, storage, security, computational power, and medico-legal issue are the major hurdles. The proper guidelines, finance, organization, and collaboration with multiple disciplines are needed to implement DL. Till date, the majority of the cytologists are not totally aware of the potential of DL. In this review, the overview of the DL system along with its potential clinical applications has been discussed.