Machine learning technique helps identify cancer cell types

Brown researchers have trained a computer algorithm to spot in laboratory samples a cellular transition associated with more aggressive cancers. Credit: Wong Lab / Brown University National Institutes of Health, COBRE Center for Cancer Research Development at Rhode Island Hospital, Rhode Island Foundation Medical Research Grant, Jason and Donna McGraw Weiss Brown University researchers have developed a new image analysis technique to distinguish two key cancer cell types associated with tumor progression. The approach could help in pre-clinical screening of cancer drugs and shed light on a cellular metamorphosis that is associated with more malignant and drug-resistant cancers. The epithelial-mesenchymal transition, or EMT, is a process by which more docile epithelial cells transform into more aggressive mesenchymal cells. Tumors with higher numbers of mesenchymal cells are often more malignant and…


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