Investigating the Usability of XAI in AI-based Image Classification

This paper investigates the usability of XAI (Explainable Artificial Intelligence) in AI-based image classification, particularly for non-experts like medical professionals. XAI provides the user of AI systems with an explanation for a particular decision. But the usability of such explanations remains an open point of discussion. The investigation highlights that there is a need for integrating explainability in the design of the classification approach. This paper will present an approach to classify the parts of an object separately and then utilize a white box model (decision tree) for the final classification. This is enriched by additional information, achieving understandability of the classification. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)