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Explainable and Trustworthy Artificial Intelligence Guest Editorial., , and . IEEE Comput. Intell. Mag., 17 (1): 14-15 (2022)Introducing User Feedback-based Counterfactual Explanations (UFCE)., , and . CoRR, (2024)Interpretable clinical time-series modeling with intelligent feature selection for early prediction of antimicrobial multidrug resistance., , , , , and . Future Gener. Comput. Syst., (2022)Measuring Model Understandability by means of Shapley Additive Explanations., , and . FUZZ-IEEE, page 1-8. IEEE, (2022)A Confusion Matrix for Evaluating Feature Attribution Methods., , , and . CVPR Workshops, page 3709-3714. IEEE, (2023)How to Build Self-Explaining Fuzzy Systems: From Interpretability to Explainability AI-eXplained., , , and . IEEE Comput. Intell. Mag., 19 (1): 81-82 (February 2024)Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges., , , , and . Artif. Intell. Rev., 56 (10): 11149-11296 (October 2023)Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence., , , , , , , , , and . Inf. Fusion, (November 2023)The Role of Speculations for Explainable and Trustworthy Artificial Intelligence: A Use Case on Art Genre Classification., and . EUSFLAT/AGOP, volume 14069 of Lecture Notes in Computer Science, page 455-467. Springer, (2023)Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP., , , , , , , , , and 29 other author(s). CoRR, (2023)