Results 261 to 270 of about 4,635,657 (309)

Predicting cardiovascular risk with hybrid ensemble learning and explainable AI

Scientific Reports
Cardiovascular diseases (CVDs) are still one of the leading causes of death globally, underscoring the importance of early and right risk prediction for effective preventive measures and therapeutic approaches.
Pooja Shah, Madhu Shukla, Neel H. Dholakia, Himanshu Gupta   +3 more
semanticscholar   +1 more source

Deep learning and explainable AI for classification of potato leaf diseases

Frontiers Artif. Intell.
The accurate classification of potato leaf diseases plays a pivotal role in ensuring the health and productivity of crops. This study presents a unified approach for addressing this challenge by leveraging the power of Explainable AI (XAI) and transfer ...
Sarah M. Alhammad, D. S. Khafaga, W. M. El-Hady, Farid M. Samy, Khalid M. Hosny   +4 more
semanticscholar   +1 more source

Explaining Explanation For “Explainable Ai”

Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2018
What makes for an explanation of “black box” AI systems such as Deep Nets? We reviewed the pertinent literatures on explanation and derived key ideas. This set the stage for our empirical inquiries, which include conceptual cognitive modeling, the analysis of a corpus of cases of "naturalistic explanation" of computational systems, computational ...
Robert R. Hoffman, Gary Klein, Shane T. Mueller   +2 more
openaire   +1 more source

Explainable AI

With the rapid development of Artificial Intelligence (AI) in many areas, demand for explainability and reliability of systems has also increased. AI Explainability (XAI) addresses the study of AI that can be understood by humans, since interpretability is essential for user trust, ethical, and legal issues.
Varnesh Ghildiyal, Abhishek Danu, Vibha Verma, Aruna Bhat   +3 more
  +7 more sources

Explainable AI chatbots towards XAI ChatGPT: A review

Heliyon
Advances in artificial intelligence (AI) have had a major impact on natural language processing (NLP), even more so with the emergence of large-scale language models like ChatGPT.
Attila Kovari
semanticscholar   +1 more source

Explainable AI (XAI) for trustworthy and transparent decision-making: A theoretical framework for AI interpretability

World Journal of Advanced Engineering Technology and Sciences
Explainable Artificial Intelligence (XAI) has become a critical area of research in addressing the black-box nature of complex AI models, particularly as these systems increasingly influence high-stakes domains such as healthcare, finance, and autonomous
Arunraju Chinnaraju
semanticscholar   +1 more source

AI, explain yourself

Communications of the ACM, 2018
It is increasingly important to understand how artificial intelligence comes to a decision.
openaire   +1 more source

Unveiling Explainable AI in Healthcare: Current Trends, Challenges, and Future Directions

WIREs Data. Mining. Knowl. Discov.
This overview investigates the evolution and current landscape of eXplainable Artificial Intelligence (XAI) in healthcare, highlighting its implications for researchers, technology developers, and policymakers.
Abdul Aziz Noor, Awais Manzoor, M. Qureshi, M. A. Qureshi, Wael Rashwan   +4 more
semanticscholar   +1 more source

Explainable AI in Manufacturing and Industrial Cyber–Physical Systems: A Survey

Electronics (Switzerland)
This survey explores applications of explainable artificial intelligence in manufacturing and industrial cyber–physical systems. As technological advancements continue to integrate artificial intelligence into critical infrastructure and industrial ...
Maryam Farajzadeh-Zanjani, Roozbeh Razavi-Far, Vasile Palade   +2 more
exaly   +2 more sources

Explainable AI for DeepFake Detection

Applied Sciences
The surge in technological advancements has resulted in concerns over its misuse in politics and entertainment, making reliable detection methods essential.
Nazneen Mansoor, Alexander I. Iliev
semanticscholar   +1 more source