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03/30/2023
Rethinking AI Explainability and Plausibility
Setting proper evaluation objectives for explainable artificial intellig...
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02/10/2023
Invisible Users: Uncovering End-Users' Requirements for Explainable AI via Explanation Forms and Goals
Non-technical end-users are silent and invisible users of the state-of-t...
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08/18/2022
Transcending XAI Algorithm Boundaries through End-User-Inspired Design
The boundaries of existing explainable artificial intelligence (XAI) alg...
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03/12/2022
Evaluating Explainable AI on a Multi-Modal Medical Imaging Task: Can Existing Algorithms Fulfill Clinical Requirements?
Being able to explain the prediction to clinical end-users is a necessit...
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02/16/2022
Guidelines and evaluation for clinical explainable AI on medical image analysis
Explainable artificial intelligence (XAI) is essential for enabling clin...
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07/11/2021
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images
Being able to explain the prediction to clinical end-users is a necessit...
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02/04/2021
EUCA: A Practical Prototyping Framework towards End-User-Centered Explainable Artificial Intelligence
The ability to explain decisions to its end-users is a necessity to depl...
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11/28/2019
Applying Artificial Intelligence to Glioma Imaging: Advances and Challenges
Primary brain tumors including gliomas continue to pose significant mana...
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04/07/2019