Domain-generalizable oral cancer classification: bridging multi-center histopathological datasets.

Researchers developed a method called SICA to improve oral cancer detection from microscopy images across different laboratories and equipment by combining multiple techniques to make the model invariant to staining and imaging variations. Testing showed the approach performed well on simulated multi-centre data but failed on truly independent data, suggesting that image scale differences pose a greater challenge than stain variations.

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