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- W4300933612 abstract "We propose “Trustworthy AI Explanations as an Interface” framework to evaluate the AI systems by comparing the explanations generated by the system with the reasoning provided by the domain experts based on their experience and expertise. The proposed framework is based on the Trustworthy Explainability Acceptance metric and helps calibrate the trust and acceptance of the system accordingly. This framework can be easily implemented to any explainable AI system and can be used by standardization organizations to test and evaluate the AI systems. We illustrate the proposed framework using an interpretable medical diagnostic system for Breast Cancer Prediction." @default.
- W4300933612 created "2022-10-04" @default.
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- W4300933612 date "2022-01-01" @default.
- W4300933612 modified "2023-09-26" @default.
- W4300933612 title "Trustworthy AI Explanations as an Interface in Medical Diagnostic Systems" @default.
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- W4300933612 doi "https://doi.org/10.1007/978-3-031-14314-4_12" @default.
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