Article

Quantifying Interpretation Reproducibility in Vision Transformer Models with TAVAC

2024-01-22

Abstract excerpt

The use of deep learning algorithms to extract meaningful diagnostic features from biomedical images holds the promise to improve patient care given the expansion of digital pathology. Among these deep learning models, Vision Transformer (ViT) models have been demonstrated to capture long-range spatial relationships with more robust prediction power for image classification tasks than regular convolutional neural...

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Literature Corpus work: 9b944496-d497-5449-8a70-4659b0c1a19b
DOI: 10.1101/2024.01.18.576252

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