Results 11 to 20 of about 23,034 (235)
The Pragmatic Turn in Explainable Artificial Intelligence (XAI) [PDF]
Minds and Machines, 2019 In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI.
Páez, Andrés
core +5 more sources
A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Recently, artificial intelligence and machine learning in general have demonstrated remarkable performances in many tasks, from image processing to natural language processing, especially with the advent of deep learning. Along with research progress, they have encroached upon many different fields and disciplines.
Erico Tjoa, Cuntai Guan
openaire +4 more sources
Editorial: Explainable Artificial Intelligence (XAI) in Systems Neuroscience. [PDF]
Front Syst Neurosci, 2021 In the last 10 years, we have experienced exceptional growth in the development of machine-learning-based (ML) algorithms for the analysis of different medical conditions and for developing clinical decision support systems. In particular, the availability of large datasets and the increasing complexity of both hardware and software systems have ...
Lombardi A, Tavares JMRS, Tangaro S.
europepmc +6 more sources
Explainable Artificial Intelligence (XAI)
Information Technology and Libraries, 2022 The field of explainable artificial intelligence (XAI) advances techniques, processes, and strategies that provide explanations for the predictions, recommendations, and decisions of opaque and complex machine learning systems. Increasingly academic libraries are providing library users with systems, services, and collections created and delivered by ...
openaire +3 more sources
eXplainable Artificial Intelligence (XAI) for improving organisational regility. [PDF]
PLoS OneSince the pandemic started, organisations have been actively seeking ways to improve their organisational agility and resilience (regility) and turn to Artificial Intelligence (AI) to gain a deeper understanding and further enhance their agility and regility. Organisations are turning to AI as a critical enabler to achieve these goals.
Shafiabady N +5 more
europepmc +6 more sources
Explaining Deep Learning-Based Driver Models
Applied Sciences, 2021 Different systems based on Artificial Intelligence (AI) techniques are currently used in relevant areas such as healthcare, cybersecurity, natural language processing, and self-driving cars.
Maria Paz Sesmero Lorente +5 more
doaj +1 more source
Review of Software Engineering Techniques and Methods Based on Explainable Artificial Intelligence [PDF]
Jisuanji kexue, 2023 In terms of information processing and decision-making,artificial intelligence(AI) methods have shown superior performance compared to traditional methods.However,when AI models are put into production,their output results are not guaranteed to be ...
XING Ying
doaj +1 more source
Applied AI Letters, 2021 The DARPA Explainable Artificial Intelligence (AI) (XAI) Program focused on generating explanations for AI programs that use machine learning techniques. This article highlights progress during the DARPA Program (2017‐2021) relative to research since the
William J. Clancey, Robert R. Hoffman
doaj +1 more source
Explainable AI for designers: A human-centered perspective on mixed-initiative co-creation [PDF]
, 2018 Growing interest in eXplainable Artificial Intelligence (XAI) aims to make AI and machine learning more understandable to human users. However, most existing work focuses on new algorithms, and not on usability, practical interpretability and efficacy on
Bidarra, Rafael +4 more
core +1 more source
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Diseases of the Gastrointestinal (GI) tract significantly affect the quality of human life and have a high fatality rate. Accurate diagnosis of GI diseases plays a pivotal role in healthcare systems. However, processing large amounts of medical image data can be challenging for radiologists and other medical professionals, increasing the risk ...
Muhammad Nouman Noor +5 more
wiley +1 more source