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A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei
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 advances in recent years. However, effec...
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| Published in: | Nat Protoc |
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| Main Authors: | , , , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8167883/ https://ncbi.nlm.nih.gov/pubmed/33424024 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41596-020-00432-x |
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