Trustworthy Explainability Acceptance: A New Metric to Measure the Trustworthiness of Interpretable AI Medical Diagnostic Systems
نویسندگان
چکیده
We propose, Trustworthy Explainability Acceptance metric to evaluate explainable AI systems using expert-in-the-loop. Our calculates acceptance by quantifying the distance between explanations generated system and reasoning provided experts based on their expertise experience. also evaluates trust of include different groups our mechanism. can be easily adapted any Interpretable used in standardization process trustworthy systems. illustrate proposed high-stake medical application Predicting Ductal Carcinoma Situ (DCIS) Recurrence. successfully captures explainability DCIS recurrence experts.
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ژورنال
عنوان ژورنال: Lecture notes in networks and systems
سال: 2021
ISSN: ['2367-3370', '2367-3389']
DOI: https://doi.org/10.1007/978-3-030-79725-6_4