Analysis of Histopathological Images​

Deep learning is increasingly used in digital pathology due to its strong predictive capabilities, but the field also requires explanations beyond just quantitative metrics. This study highlights how explanation methods, particularly heatmaps, can address biases commonly found in histopathological image data, improving model generalization and accuracy. By focusing on pixel-wise heatmaps, these techniques not only detect, but also help mitigate biases, enhancing the reliability and effectiveness of deep learning models in digital pathology.