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Survey on explainable knowledge graph reasoning methods
In recent years, deep learning models have achieved remarkable progress in the prediction and classification tasks of artificial intelligence systems.However, most of the current deep learning models are black box, which means it is not conducive to ...
Yi XIA +5 more
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Discovering Themes in Deep Brain Stimulation Research Using Explainable Artificial Intelligence
Deep brain stimulation is a treatment that controls symptoms by changing brain activity. The complexity of how to best treat brain dysfunction with deep brain stimulation has spawned research into artificial intelligence approaches. Machine learning is a
Ben Allen
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Unlocking the Potential of Explainable Artificial Intelligence in Remote Sensing Big Data
In the ever-evolving landscape of artificial intelligence and big data, the concept of explainable artificial intelligence (XAI) [...]
Peng Liu, Lizhe Wang, Jun Li
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Stroke presents a formidable global health threat, carrying significant risks and challenges. Timely intervention and improved outcomes hinge on the integration of Explainable Artificial Intelligence (XAI) into medical decision-making.
Daraje Kaba Gurmessa, Worku Jimma
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Exploring Explainable Artificial Intelligence for Transparent Decision Making [PDF]
Artificial intelligence (AI) has become a potent tool in many fields, allowing complicated tasks to be completed with astounding effectiveness. However, as AI systems get more complex, worries about their interpretability and transparency have become ...
Praveenraj D. David Winster +6 more
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Explainable Artificial Intelligence in education
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms.
Hassan Khosravi +9 more
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A novel explainable COVID-19 diagnosis method by integration of feature selection with random forest
Several Artificial Intelligence-based models have been developed for COVID-19 disease diagnosis. In spite of the promise of artificial intelligence, there are very few models which bridge the gap between traditional human-centered diagnosis and the ...
Mehrdad Rostami, Mourad Oussalah
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EvalAttAI: A Holistic Approach to Evaluating Attribution Maps in Robust and Non-Robust Models
The expansion of explainable artificial intelligence as a field of research has generated numerous methods of visualizing and understanding the black box of a machine learning model.
Ian E. Nielsen +4 more
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Explainable Artificial Intelligence in the Early Diagnosis of Gastrointestinal Disease
This study reviews the recent progress of explainable artificial intelligence for the early diagnosis of gastrointestinal disease (GID). The source of data was eight original studies in PubMed.
Kwang-Sig Lee, Eun Sun Kim
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Explainable Artificial Intelligence (XAI) in Insurance
Explainable Artificial Intelligence (XAI) models allow for a more transparent and understandable relationship between humans and machines. The insurance industry represents a fundamental opportunity to demonstrate the potential of XAI, with the industry ...
Emer Owens +5 more
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