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Comparing Interpretable AI Approaches for the Clinical Environment: an Application to COVID-19.

, , , , , , and . CIBCB, page 1-8. IEEE, (2022)

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Trustworthy Artificial Intelligence in Medical Applications: A Mini Survey., , , and . CIBCB, page 1-8. IEEE, (2023)A data-driven decision support framework for DEA target setting: an explainable AI approach., , and . Eng. Appl. Artif. Intell., 127 (Part A): 107222 (January 2024)A fuzzy cognitive map based on Nash bargaining game for supplier selection problem: a case study on auto parts industry., and . Oper. Res., 22 (3): 2133-2171 (2022)Comparing Interpretable AI Approaches for the Clinical Environment: an Application to COVID-19., , , , , , and . CIBCB, page 1-8. IEEE, (2022)Implementing bargaining game-based fuzzy cognitive map and mixed-motive games for group decisions in the healthcare supplier selection., and . Artif. Intell. Rev., 56 (10): 11739-11772 (October 2023)Uncovering the Hidden Significance of Activities Location in Predictive Process Monitoring., , , , and . ICPM Workshops, volume 503 of Lecture Notes in Business Information Processing, page 191-203. Springer, (2023)Risk assessment in discrete production processes considering uncertainty and reliability: Z-number multi-stage fuzzy cognitive map with fuzzy learning algorithm., , and . Artif. Intell. Rev., 54 (2): 1349-1383 (2021)Measuring Perceived Trust in XAI-Assisted Decision-Making by Eliciting a Mental Model., , , and . CoRR, (2023)