Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study
Description
Recent advances in artificial intelligence (AI) have sparked interest in developing explainable AI (XAI) methods for clinical decision support systems, especially in translational research. Although using XAI methods may enhance trust in black-box