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Currently, we use only one of the DP feature sets for linear modeling and power analysis. We should use both.
It would also be good to clarify what is different between the feature spaces. Are there differences per single cell feature? This might help us to zero in on efficientnet features that are significantly capturing nuclei or cytoplasm!
The text was updated successfully, but these errors were encountered:
This is something that we should have analysis for. The difference in the DP feature sets is what object is used to measure the features. So nuc project uses nuclei objects and cyto project uses whole cell objects.
So essentially this is like CP where there are different objects but there are two different outputs since DP can only run one object at a time.
Currently, we use only one of the DP feature sets for linear modeling and power analysis. We should use both.
It would also be good to clarify what is different between the feature spaces. Are there differences per single cell feature? This might help us to zero in on efficientnet features that are significantly capturing nuclei or cytoplasm!
The text was updated successfully, but these errors were encountered: