Science Daily explores the issue in more depth (4 July 2017): "However, because the artificial intelligence system is a technique which analyses the embryo through mathematical variables, it offers low subjectivity and high repeatability, making embryo classification more consistent. "Nevertheless," said Professor Rocha, "the artificial intelligence system must be based on learning from a human being -- that is, the experienced embryologists who set the standards of assessment to train the system."" See also EurekAlert (4 July 2017): "The system utilizes a sophisticated architecture of multi-class deep neural networks (DNNs) and DNN ensembles trained on thousands of samples of carefully selected cells of multiple classes: embryonic stem cells, induced pluripotent stem cells, progenitor stem cells, adult stem cells and adult cells to recognize the class and embryonic state of the sample, achieving high accuracy in simulations. The unique samples were generated using standardized protocols by BioTime, Inc. and profiled on a single microarray platform. The sample sets were augmented with carefully selected and manually curated data from public repositories coming from multiple experiments and generated on different platforms.
Jul-17-2017, 09:35:12 GMT