Survey of explainable AI techniques in healthcare

A Chaddad, J Peng, J Xu, A Bouridane - Sensors, 2023‏ - mdpi.com
Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …

Towards a science of human-AI decision making: An overview of design space in empirical human-subject studies

V Lai, C Chen, A Smith-Renner, QV Liao… - Proceedings of the 2023 …, 2023‏ - dl.acm.org
AI systems are adopted in numerous domains due to their increasingly strong predictive
performance. However, in high-stakes domains such as criminal justice and healthcare, full …

Towards human-centered explainable ai: A survey of user studies for model explanations

Y Rong, T Leemann, TT Nguyen… - IEEE transactions on …, 2023‏ - ieeexplore.ieee.org
Explainable AI (XAI) is widely viewed as a sine qua non for ever-expanding AI research. A
better understanding of the needs of XAI users, as well as human-centered evaluations of …

Are explanations helpful? a comparative study of the effects of explanations in ai-assisted decision-making

X Wang, M Yin - Proceedings of the 26th International Conference on …, 2021‏ - dl.acm.org
This paper contributes to the growing literature in empirical evaluation of explainable AI
(XAI) methods by presenting a comparison on the effects of a set of established XAI methods …

Expanding explainability: Towards social transparency in ai systems

U Ehsan, QV Liao, M Muller, MO Riedl… - Proceedings of the 2021 …, 2021‏ - dl.acm.org
As AI-powered systems increasingly mediate consequential decision-making, their
explainability is critical for end-users to take informed and accountable actions. Explanations …