What Techniques are Used in Explainable AI for Histology?
Several techniques are employed to make AI decisions in histology more transparent:
1. Saliency Maps: These highlight the areas of an image that the AI model considers important for its decision. For example, a saliency map can show which regions of a biopsy the AI focused on to diagnose cancer. 2. Layer-wise Relevance Propagation (LRP): This technique breaks down the AI's decision-making process layer by layer, explaining how each part of the image contributed to the final decision. 3. Decision Trees: While not as common in image analysis, decision trees can be used in conjunction with other AI models to provide a step-by-step rationale for decisions.
