Nature, 22 February 2018, Vol.554(7693), pp.555-557
TRAINING SMART ALGORITHMS Deep-learning algorithms (see 'Deep thoughts') rely on neural networks, a computational model first proposed in the 1940s, in which layers of neuron-like nodes mimic how human brains analyse information. [...]about five years ago, machine-learning algorithms based on neural networks relied on researchers to process the raw information into a more meaningful form before feeding it into the computational models, says Casey Greene, a computational biologist at the University of Pennsylvania in Philadelphia. [...]in 2005, Anne Carpenter, a computational biologist at the Broad Institute of MIT and Harvard in Cambridge, Massachusetts, released an open-source software package called CellProfiler to help biologists to quantitatively measure individual features: the number of fluorescent cells in a microscopy field, for example, or the length of a zebrafish. Mark DePristo, who heads deep-learning-based genomic research at Verily, expects DeepVariant to be particularly useful...
Machine Learning ; Biology -- Methods ; Image Interpretation, Computer-Assisted -- Methods
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