Explainable artificial intelligence: a comprehensive review

D Minh, HX Wang, YF Li, TN Nguyen - Artificial Intelligence Review, 2022‏ - Springer
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …

[HTML][HTML] Large language models in law: A survey

J Lai, W Gan, J Wu, Z Qi, SY Philip - AI Open, 2024‏ - Elsevier
The advent of artificial intelligence (AI) has significantly impacted the traditional judicial
industry. Moreover, recently, with the development of the concept of AI-generated content …

Generative ai

S Feuerriegel, J Hartmann, C Janiesch… - Business & Information …, 2024‏ - Springer
Tom Freston is credited with saying ''Innovation is taking two things that exist and putting
them together in a new way''. For a long time in history, it has been the prevailing …

A survey of explainable artificial intelligence for smart cities

AR Javed, W Ahmed, S Pandya, PKR Maddikunta… - Electronics, 2023‏ - mdpi.com
The emergence of Explainable Artificial Intelligence (XAI) has enhanced the lives of humans
and envisioned the concept of smart cities using informed actions, enhanced user …

A systematic review of explainable artificial intelligence in terms of different application domains and tasks

MR Islam, MU Ahmed, S Barua, S Begum - Applied Sciences, 2022‏ - mdpi.com
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved
and are now being employed in almost every application domain to develop automated or …

A framework for AI-powered service innovation capability: Review and agenda for future research

S Akter, MA Hossain, S Sajib, S Sultana, M Rahman… - Technovation, 2023‏ - Elsevier
Artificial intelligence (AI)-powered service innovation (eg, OpenAI's ChatGPT, Google's Bard
and Microsoft's Sydney) has become one of the most significant determinants of firms' …

[HTML][HTML] Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks

S Nazir, DM Dickson, MU Akram - Computers in Biology and Medicine, 2023‏ - Elsevier
Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …

Explainability in graph neural networks: A taxonomic survey

H Yuan, H Yu, S Gui, S Ji - IEEE transactions on pattern …, 2022‏ - ieeexplore.ieee.org
Deep learning methods are achieving ever-increasing performance on many artificial
intelligence tasks. A major limitation of deep models is that they are not amenable to …

[HTML][HTML] Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond

G Yang, Q Ye, J **a - Information Fusion, 2022‏ - Elsevier
Abstract Explainable Artificial Intelligence (XAI) is an emerging research topic of machine
learning aimed at unboxing how AI systems' black-box choices are made. This research field …

A strategic framework for artificial intelligence in marketing

MH Huang, RT Rust - Journal of the Academy of Marketing Science, 2021‏ - Springer
The authors develop a three-stage framework for strategic marketing planning, incorporating
multiple artificial intelligence (AI) benefits: mechanical AI for automating repetitive marketing …