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CLAM is a high-throughput and interpretable method for data efficient whole slide image (WSI) classification using slide-level labels without any ROI extraction or patch-level annotations, and is capable of handling multi-class subtyping problems.

CLAM is available as a module which wraps an Apptainer container on Apocrita.


To run the default installed version of CLAM, simply load the clam module:

$ module load clam
$ clam
[python output]

Example job

Serial job

Here is an example job running on 1 core and 1GB of memory, using the built-in Python3 interpreter:

#$ -cwd
#$ -j y
#$ -pe smp 1
#$ -l h_vmem=1G
#$ -l h_rt=1:0:0

module load clam