Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey
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 …
[HTML][HTML] How to explain AI systems to end users: a systematic literature review and research agenda
S Laato, M Tiainen, AKM Najmul Islam… - Internet …, 2022 - emerald.com
Purpose Inscrutable machine learning (ML) models are part of increasingly many
information systems. Understanding how these models behave, and what their output is …
information systems. Understanding how these models behave, and what their output is …
[HTML][HTML] Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research
The rapid growth and use of artificial intelligence (AI)-based systems have raised concerns
regarding explainability. Recent studies have discussed the emerging demand for …
regarding explainability. Recent studies have discussed the emerging demand for …
A survey on explainable artificial intelligence (xai): Toward medical xai
Recently, artificial intelligence and machine learning in general have demonstrated
remarkable performances in many tasks, from image processing to natural language …
remarkable performances in many tasks, from image processing to natural language …
A review on explainable artificial intelligence for healthcare: why, how, and when?
S Bharati, MRH Mondal… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Artificial intelligence (AI) models are increasingly finding applications in the field of
medicine. Concerns have been raised about the explainability of the decisions that are …
medicine. Concerns have been raised about the explainability of the decisions that are …
[HTML][HTML] A review of explainable deep learning cancer detection models in medical imaging
Deep learning has demonstrated remarkable accuracy analyzing images for cancer
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
Reviewing the need for explainable artificial intelligence (xAI)
The diffusion of artificial intelligence (AI) applications in organizations and society has fueled
research on explaining AI decisions. The explainable AI (xAI) field is rapidly expanding with …
research on explaining AI decisions. The explainable AI (xAI) field is rapidly expanding with …
[HTML][HTML] Argumentation approaches for explanaible AI in medical informatics
Artificial Intelligence algorithms are powerful in performing accurate predictions, but they are
often considered black boxes as they do not provide any explanation about how outputs are …
often considered black boxes as they do not provide any explanation about how outputs are …
What are people doing about XAI user experience? A survey on AI explainability research and practice
JJ Ferreira, MS Monteiro - Design, User Experience, and Usability. Design …, 2020 - Springer
Explainability is a hot topic nowadays for artificial intelligent (AI) systems. The role of
machine learning (ML) models on influencing human decisions shed light on the back-box …
machine learning (ML) models on influencing human decisions shed light on the back-box …
Explainable artificial intelligence (XAI): An engineering perspective
The remarkable advancements in Deep Learning (DL) algorithms have fueled enthusiasm
for using Artificial Intelligence (AI) technologies in almost every domain; however, the …
for using Artificial Intelligence (AI) technologies in almost every domain; however, the …