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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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| Publicat a: | Nat Protoc |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2021
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| Matèries: | |
| Accés en línia: | 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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