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SeyedehRoksana Mirzaei, Hua Mao, Raid Rafi Omar Al-Nima and Wai Lok Woo
Explainable Artificial Intelligence (XAI) evaluation has grown significantly due to its extensive adoption, and the catastrophic consequence of misinterpreting sensitive data, especially in the medical field. However, the multidisciplinary nature of XAI ...
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Hamad Almaghrabi, Ben Soh and Alice Li
Effective and efficient use of information and communication technology (ICT) systems in the administration of educational organisations is crucial to optimise their performance. Earlier research on the identification and analysis of ICT users? satisfact...
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Marwah Abdulrazzaq Naser, Aso Ahmed Majeed, Muntadher Alsabah, Taha Raad Al-Shaikhli and Kawa M. Kaky
Cardiovascular disease is the leading cause of global mortality and responsible for millions of deaths annually. The mortality rate and overall consequences of cardiac disease can be reduced with early disease detection. However, conventional diagnostic ...
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Romy Müller, Marcel Dürschmidt, Julian Ullrich, Carsten Knoll, Sascha Weber and Steffen Seitz
Deep neural networks are powerful image classifiers but do they attend to similar image areas as humans? While previous studies have investigated how this similarity is shaped by technological factors, little is known about the role of factors that affec...
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Fátima Trindade Neves, Manuela Aparicio and Miguel de Castro Neto
In the rapidly evolving landscape of urban development, where smart cities increasingly rely on artificial intelligence (AI) solutions to address complex challenges, using AI to accurately predict real estate prices becomes a multifaceted and crucial tas...
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Hamed Taherdoost and Mitra Madanchian
In recent years, artificial intelligence (AI) has seen remarkable advancements, stretching the limits of what is possible and opening up new frontiers. This comparative review investigates the evolving landscape of AI advancements, providing a thorough e...
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Cédric Roussel and Klaus Böhm
Explainable Artificial Intelligence (XAI) has the potential to open up black-box machine learning models. XAI can be used to optimize machine learning models, to search for scientific findings, or to improve the understandability of the AI system for the...
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Ezekiel Bernardo and Rosemary Seva
Explainable Artificial Intelligence (XAI) has successfully solved the black box paradox of Artificial Intelligence (AI). By providing human-level insights on AI, it allowed users to understand its inner workings even with limited knowledge of the machine...
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Vidhya Kamakshi and Narayanan C. Krishnan
Explainable Artificial Intelligence (XAI) has emerged as a crucial research area to address the interpretability challenges posed by complex machine learning models. In this survey paper, we provide a comprehensive analysis of existing approaches in the ...
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Tim Hulsen
Artificial Intelligence (AI) describes computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Examples of AI techniques are machine learni...
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