A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei.
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DOI: 10.1038/s41596-020-00432-x
Abstract: Cell morphology encodes essential information on many underlying biological processes. It is commonly used by clinicians and researchers in the study, diagnosis, prognosis, and treatment of human diseases. Quantification of cell morphology has seen tremendous… read more here.
Keywords: machine learning; robust unsupervised; unsupervised machine; morphological heterogeneity ... See more keywords