A survey of visual analytics for explainable artificial intelligence methods
G Alicioglu, B Sun - Computers & Graphics, 2022 - Elsevier
Deep learning (DL) models have achieved impressive performance in various domains such
as medicine, finance, and autonomous vehicle systems with advances in computing power …
as medicine, finance, and autonomous vehicle systems with advances in computing power …
Machine learning interpretability: A survey on methods and metrics
Machine learning systems are becoming increasingly ubiquitous. These systems's adoption
has been expanding, accelerating the shift towards a more algorithmic society, meaning that …
has been expanding, accelerating the shift towards a more algorithmic society, meaning that …
[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …
applications, but the outcomes of many AI models are challenging to comprehend and trust …
Explainable artificial intelligence: a systematic review
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …
years. This is due to the widespread application of machine learning, particularly deep …
Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey
W Ding, M Abdel-Basset, H Hawash, AM Ali - Information Sciences, 2022 - Elsevier
The continuous advancement of Artificial Intelligence (AI) has been revolutionizing the
strategy of decision-making in different life domains. Regardless of this achievement, AI …
strategy of decision-making in different life domains. Regardless of this achievement, AI …
Designing theory-driven user-centric explainable AI
From healthcare to criminal justice, artificial intelligence (AI) is increasingly supporting high-
consequence human decisions. This has spurred the field of explainable AI (XAI). This …
consequence human decisions. This has spurred the field of explainable AI (XAI). This …
Recent advances in trustworthy explainable artificial intelligence: Status, challenges, and perspectives
Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier
days of conceptual theories, to being an integral part of today's technological society. Rapid …
days of conceptual theories, to being an integral part of today's technological society. Rapid …
A multidisciplinary survey and framework for design and evaluation of explainable AI systems
The need for interpretable and accountable intelligent systems grows along with the
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …
Opportunities and obstacles for deep learning in biology and medicine
T Ching, DS Himmelstein… - Journal of the …, 2018 - royalsocietypublishing.org
Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …
combining raw inputs into layers of intermediate features. These algorithms have recently …
A survey of visual analytics techniques for machine learning
Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …
in the field of visualization. To better identify which research topics are promising and to …