Towards explainable artificial intelligence through expert-augmented supervised feature selection

M Rabiee, M Mirhashemi, MS Pangburn, S Piri… - Decision Support …, 2024 - Elsevier
This paper presents a comprehensive framework for expert-augmented supervised feature
selection, addressing pre-processing, in-processing, and post-processing aspects of …

A roadmap of explainable artificial intelligence: Explain to whom, when, what and how?

Z Wang, C Huang, X Yao - ACM Transactions on Autonomous and …, 2024 - dl.acm.org
Explainable artificial intelligence (XAI) has gained significant attention, especially in AI-
powered autonomous and adaptive systems (AASs). However, a discernible disconnect …

[HTML][HTML] Explainable artificial intelligence for machine learning prediction of bandgap energies

T Masuda, K Tanabe - Journal of Applied Physics, 2024 - pubs.aip.org
The bandgap is an inherent property of semiconductors and insulators, significantly
influencing their electrical and optical characteristics. However, theoretical calculations …

XAI based feature selection for gestational diabetes Mellitus prediction

A Maaloul, M Jemel, NB Azzouna - 2024 10th International …, 2024 - ieeexplore.ieee.org
Gestational Diabetes Mellitus (GDM) is a type of diabetes that develops during pregnancy. It
is important for pregnant women to monitor their blood sugar levels regularly and follow a …