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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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@Phys_org@feeds.twtxt.net Lousy headline. Neural networks don’t learn anything. They are not sentient, nor do they have drive or will. You wouldn’t say “Gaussian distribution learns mean and variance” so don’t phrase headlines like this.