Tertiary Review on Explainable Artificial Intelligence: Where Do We Stand? by Frank van Mourik, Annemarie Jutte, Stijn E. Berendse, Faiza A. Bukhsh, Faizan Ahmed

Subjects: “…explainable AI…”
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Detection of Alzheimer’s Disease using Explainable Machine Learning and Mathematical Models by Krishna Mahapatra, R. Selvakumar

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Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis by C. R. Dhivyaa, K. Nithya, C. Sathiya Kumar, R. Sudhakar

“…The proposed model yields a remarkable average accuracy value of 98.80%. Furthermore, explainable Artificial Intelligence experiments validate the effectiveness of the proposed diagnostic approach.…”
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A lightweight and explainable CNN model for empowering plant disease diagnosis by Chiranjit Pal, Swastik Karmakar, Imon Mukherjee, Partha Pratim Chakrabarti

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Enhancing automatic early arteriosclerosis prediction: an explainable machine learning evidence by Eka Miranda, Suko Adiarto

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Support of individual educational trajectories based on the concept of explainable artificial intelligence by I. G. Zakharova, M. S. Vorobeva, Yu. V. Boganyuk

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Meta-regression to explain shrinkage and heterogeneity in large-scale replication projects. by Rachel Heyard, Leonhard Held

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Explaining training and adjustment diversity in multinational enterprises: literal and figurative interpretations by Symeon Mandrinos, Constance Liew Sat Lin, Nurul Ilma binti Salleh

“…Purpose – This study emphasises the importance of both literal and figurative interpretations in explaining training and adjustment (cross-cultural) diversity in a multinational enterprise (MNE) context. …”
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Diffusion-based mechanism explains spatial organization in cross-feeding biofilms by Julio Pérez, Cristian Picioreanu

“…Abstract Complex symbiotic interactions were claimed for explaining spatial organization of microbial species in cross-feeding biofilms. …”
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Supercooled phase transitions in conformal dark sectors explain NANOGrav data by João Gonçalves, Danny Marfatia, António P. Morais, Roman Pasechnik

“…According to recent lore, it is difficult to explain the evidence for a stochastic gravitational wave background obtained by pulsar timing arrays with supercooled first-order phase transitions (FOPTs). …”
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Customization of health insurance premiums using machine learning and explainable AI by Manohar Kapse, Vinod Sharma, Rutuj Vidhale, Varun Vellanki

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Detection of breast cancer using machine learning and explainable artificial intelligence by Tharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, D. Cenitta, Rajagopala Chadaga, K. S. Swathi

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Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence by Silvia García-Méndez, Francisco de Arriba-Pérez

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A predictive model for damp risk in english housing with explainable AI by Gulala Aziz, Adam Hardy

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REVISITING THEORIES AND BUILDING A NEW RESEARCH AGENDA FOR EXPLAINING RADICALIZATION by Ioana CHIȚĂ

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Explainable artificial intelligence for predicting medical students’ performance in comprehensive assessments by Haniye Mastour, Toktam Dehghani, Ehsan Moradi, Saeid Eslami

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An Application of 3D Vision Transformers and Explainable AI in Prosthetic Dentistry by Faisal Ahmed Sifat, Md Sahadul Hasan Arian, Saif Ahmed, Taseef Hasan Farook, Nabeel Mohammed, James Dudley

“…Independent CNNs and vision transformers (ViTs), and their combination (CNN and ViT hybrid model) were implemented to classify the 3D scans directly from standard tessellation language (.stl) files and an Explainable AI (ExAI) model was generated to qualitatively explore the deterministic patterns that influenced the outcomes of the automation process. …”
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The Silent Benefactor: Why Explaining the Importance of Metrology Involves Addressing the Counterfactual by Richard J. C. Brown, Paul J. Brewer

“…A different way of explaining the indispensability of metrology is therefore needed. …”
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Delayed response and biosonar perception explain movement coordination in trawling bats. by Luca Giuggioli, Thomas J McKetterick, Marc Holderied

“…Animal coordinated movement interactions are commonly explained by assuming unspecified social forces of attraction, repulsion and alignment with parameters drawn from observed movement data. …”
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XAI-FruitNet: An explainable deep model for accurate fruit classification by Shirin Sultana, Md All Moon Tasir, S.M. Nuruzzaman Nobel, Md Mohsin Kabir, M.F. Mridha

“…Through rigorous experimentation, we demonstrate that XAI-FruitNet advances state-of-the-art fruit classification accuracy and sets a new standard for explainable artificial intelligence (XAI) in agricultural applications. …”
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