Soft Tissue B/M

Summary

We are attempting to classify benign vs malignant in soft tissue slides.

Training Accuracy 100– 1000 tiles per slide
Validation Accuracy 100 – 1000 tiles per slide

The training accuracy seems to improve, especially with the 1000 tiles data set. However, validation is another story. It is clear that nothing useful is being learned by the models.

Dataset

We have a limited number (~200) slides to work with on this project and unfortunately very few of the slides are the same body part. 

I am told that most soft tissue slides are mostly tumor, so B/M methods for many organ and tissue types that look for tumors don’t yield good results.

Performance

The only positive here is that in attempts to generate something better than a coin flip, we spent the time to develop model code that would run across and (almost) full utilize many GPUs.

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