Results 31 to 40 of about 24,682 (247)
XAITK: The explainable AI toolkit
Applied AI Letters, 2021 Recent advances in artificial intelligence (AI), driven mainly by deep neural networks, have yielded remarkable progress in fields, such as computer vision, natural language processing, and reinforcement learning.
Brian Hu +5 more
doaj +1 more source
Explainable AI Over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions
IEEE Open Journal of the Communications Society, 2022 Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines. As the number of connected devices keeps on growing, the Internet of Things (IoT) market needs to be ...
Senthil Kumar Jagatheesaperumal +5 more
doaj +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Advanced Science, EarlyView.Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Big Data and Cognitive ComputingArtificial intelligence (AI) encompasses the development of systems that perform tasks typically requiring human intelligence, such as reasoning and learning.
Sayda Umma Hamida +4 more
doaj +1 more source
Explainable Artificial Intelligence for Patient Safety: A Review of Application in Pharmacovigilance
IEEE Access, 2023 Explainable AI (XAI) is a methodology that complements the black box of artificial intelligence, and its necessity has recently been highlighted in various fields.
Seunghee Lee +5 more
doaj +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Explainable AI for Cyber-Physical Systems: Issues and Challenges
IEEE AccessArtificial intelligence and cyber-physical systems (CPS) are two of the key technologies of the future that are enabling major global shifts. However, most of the current implementations of AI in CPS are not explainable, which creates serious problems in
Amber Hoenig +4 more
doaj +1 more source
Applications of Explainable Artificial Intelligence in Diagnosis and Surgery
Diagnostics, 2022 In recent years, artificial intelligence (AI) has shown great promise in medicine. However, explainability issues make AI applications in clinical usages difficult.
Yiming Zhang, Ying Weng, Jonathan Lund
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Explainable Artificial Intelligence (XAI): An Engineering Perspective
, 2021 The remarkable advancements in Deep Learning (DL) algorithms have fueled enthusiasm for using Artificial Intelligence (AI) technologies in almost every domain; however, the opaqueness of these algorithms put a question mark on their applications in safety-critical systems.
Hussain, F., Hussain, R., Hossain, E.
openaire +2 more sources
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source