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Neural network learns how to identify chromatid cohesion defects
Scientists from Tokyo Metropolitan University have used machine learning to automate the identification of defects in sister chromatid cohesion. They trained a convolutional neural network (CNN) with microscopy images of individual stained chromosomes, identified by researchers as having or not having cohesion defects. After training, it was able to successfully classify 73.1% of new images. Automation promises better statistic … ⌘ Read more

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