research
∙
03/30/2023
Rethinking AI Explainability and Plausibility
Setting proper evaluation objectives for explainable artificial intellig...
share
research
∙
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...
research
∙
08/18/2022
Transcending XAI Algorithm Boundaries through End-User-Inspired Design
The boundaries of existing explainable artificial intelligence (XAI) alg...
research
∙
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...
research
∙
02/16/2022
Guidelines and evaluation for clinical explainable AI on medical image analysis
Explainable artificial intelligence (XAI) is essential for enabling clin...
research
∙
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...
research
∙
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...
research
∙
11/28/2019
Applying Artificial Intelligence to Glioma Imaging: Advances and Challenges
Primary brain tumors including gliomas continue to pose significant mana...
research
∙
04/07/2019
