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Contrastingly, a convolutional neural network (CNN) algorithm can automatically extract the image features and produce highly accurate image recognition. Thus, this study implements CNN to establish stable and reproducible cell culture experiments by predicting a unique morphology of pluripotent stem cell (PSC) lines. Interestingly, the algorithm distinguishes the PSC lines cultured in the different cell culture conditions, such as the presence or absence of small molecules and\/or the long\u2010 or short\u2010term culture in our induced PSC (iPSC) models, which include iPSC lines with abnormal gene expression patterns and genomic abnormalities. Our deep learning technology accurately classifies the various cell lines with or without genetic defects using only the cell images, without any labeling process. 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