Enhancing histopathological image analysis: An explainable vision transformer approach with comprehensive interpretation methods and evaluation of explanation quality

Deep learning models are increasingly reshaping medical imaging, with growing attention on ensuring transparency and trust in their decision-making processes. This study presents the Explainable Vision Transformer (XViT), a model specifically designed for histopathological image analysis. By incorpo...

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Bibliographic Details
Published in:Engineering applications of artificial intelligence 2025-06, Vol.149, p.110519, Article 110519
Main Authors: Mir, Aqib Nazir, Rizvi, Danish Raza, Ahmad, Md Rizwan
Format: Article
Language:English
Subjects:
Explainable artificial intelligence
Histopathology
Interpretability metrics
Model explainability
Vision transformer
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