GANterfactual-Counterfactual Explanations for Medical Non-experts Using Generative Adversarial Learning.

ABSTRACT: With the ongoing rise of machine learning, the need for methods for explaining decisions made by artificial intelligence systems is becoming a more and more important topic. Especially for image classification tasks, many state-of-the-art tools to explain such classifiers rely on visual highlighting of important areas of the input data. Contrary, counterfactual explanation systems try to enable a counterfactual reasoning by modifying the input image in a way such that the classifier would have made a different prediction. By doing so, the users of counterfactual explanation systems are equipped with a completely different kind of explanatory information. However, methods for generating realistic counterfactual explanations for image classifiers are still rare. Especially in medical context

SUBMITTER: Mertes S 

PROVIDER: S-EPMC9024220 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature